This paper presents a novel family of bivariate continuous Lomax generators known as the BFGMLG family, which is constructed using univariate Lomax generator (LG) families and the Farlie Gumbel Morgenstern (FGM) copula. We have derived several structural statistical properties of our proposed bivariate family, such as marginals, conditional distribution, conditional expectation, product moments, moment generating function, correlation, reliability function, and hazard rate function. The paper also introduces four special submodels of the new family based on the Weibull, exponential, Pareto, and log-logistic baseline distributions. The study establishes metrics for local dependency and examines the significant characteristics of the proposed bivariate model. To provide greater flexibility, a multivariate version of the continuous FGMLG family are suggested. Bayesian and maximum likelihood methods are employed to estimate the model parameters, and a Monte Carlo simulation evaluates the performance of the proposed bivariate family. Finally, the practical application of the proposed bivariate family is demonstrated through the analysis of four data sets.
Citation: Aisha Fayomi, Ehab M. Almetwally, Maha E. Qura. A novel bivariate Lomax-G family of distributions: Properties, inference, and applications to environmental, medical, and computer science data[J]. AIMS Mathematics, 2023, 8(8): 17539-17584. doi: 10.3934/math.2023896
[1] | Ibrahim-Elkhalil Ahmed, Ahmed E. Abouelregal, Doaa Atta, Meshari Alesemi . A fractional dual-phase-lag thermoelastic model for a solid half-space with changing thermophysical properties involving two-temperature and non-singular kernels. AIMS Mathematics, 2024, 9(3): 6964-6992. doi: 10.3934/math.2024340 |
[2] | Kamal Shah, Muhammad Sher, Muhammad Sarwar, Thabet Abdeljawad . Analysis of a nonlinear problem involving discrete and proportional delay with application to Houseflies model. AIMS Mathematics, 2024, 9(3): 7321-7339. doi: 10.3934/math.2024355 |
[3] | Rabia Noureen, Muhammad Nawaz Naeem, Dumitru Baleanu, Pshtiwan Othman Mohammed, Musawa Yahya Almusawa . Application of trigonometric B-spline functions for solving Caputo time fractional gas dynamics equation. AIMS Mathematics, 2023, 8(11): 25343-25370. doi: 10.3934/math.20231293 |
[4] | Sara S. Alzaid, Pawan Kumar Shaw, Sunil Kumar . A study of Ralston's cubic convergence with the application of population growth model. AIMS Mathematics, 2022, 7(6): 11320-11344. doi: 10.3934/math.2022632 |
[5] | Najat Almutairi, Sayed Saber . Chaos control and numerical solution of time-varying fractional Newton-Leipnik system using fractional Atangana-Baleanu derivatives. AIMS Mathematics, 2023, 8(11): 25863-25887. doi: 10.3934/math.20231319 |
[6] | Reetika Chawla, Komal Deswal, Devendra Kumar, Dumitru Baleanu . A novel finite difference based numerical approach for Modified Atangana- Baleanu Caputo derivative. AIMS Mathematics, 2022, 7(9): 17252-17268. doi: 10.3934/math.2022950 |
[7] | Shabir Ahmad, Aman Ullah, Ali Akgül, Manuel De la Sen . A study of fractional order Ambartsumian equation involving exponential decay kernel. AIMS Mathematics, 2021, 6(9): 9981-9997. doi: 10.3934/math.2021580 |
[8] | Abdelatif Boutiara, Mohammed M. Matar, Jehad Alzabut, Mohammad Esmael Samei, Hasib Khan . On ABC coupled Langevin fractional differential equations constrained by Perov's fixed point in generalized Banach spaces. AIMS Mathematics, 2023, 8(5): 12109-12132. doi: 10.3934/math.2023610 |
[9] | Muath Awadalla, Abdul Hamid Ganie, Dowlath Fathima, Adnan Khan, Jihan Alahmadi . A mathematical fractional model of waves on Shallow water surfaces: The Korteweg-de Vries equation. AIMS Mathematics, 2024, 9(5): 10561-10579. doi: 10.3934/math.2024516 |
[10] | M. Mossa Al-Sawalha, Osama Y. Ababneh, Rasool Shah, Amjad khan, Kamsing Nonlaopon . Numerical analysis of fractional-order Whitham-Broer-Kaup equations with non-singular kernel operators. AIMS Mathematics, 2023, 8(1): 2308-2336. doi: 10.3934/math.2023120 |
This paper presents a novel family of bivariate continuous Lomax generators known as the BFGMLG family, which is constructed using univariate Lomax generator (LG) families and the Farlie Gumbel Morgenstern (FGM) copula. We have derived several structural statistical properties of our proposed bivariate family, such as marginals, conditional distribution, conditional expectation, product moments, moment generating function, correlation, reliability function, and hazard rate function. The paper also introduces four special submodels of the new family based on the Weibull, exponential, Pareto, and log-logistic baseline distributions. The study establishes metrics for local dependency and examines the significant characteristics of the proposed bivariate model. To provide greater flexibility, a multivariate version of the continuous FGMLG family are suggested. Bayesian and maximum likelihood methods are employed to estimate the model parameters, and a Monte Carlo simulation evaluates the performance of the proposed bivariate family. Finally, the practical application of the proposed bivariate family is demonstrated through the analysis of four data sets.
In his survey-cum-expository review article, Srivastava [1] presented and motivated about brief expository overview of the classical q -analysis versus the so-called (p,q)-analysis with an obviously redundant additional parameter p. We also briefly consider several other families of such extensively and widely-investigated linear convolution operators as (for example) the Dziok-Srivastava, Srivastava-Wright and Srivastava-Attiya linear convolution operators, together with their extended and generalized versions. The theory of (p,q)-analysis has important role in many areas of mathematics and physics. Our usages here of the q-calculus and the fractional q-calculus in geometric function theory of complex analysis are believed to encourage and motivate significant further developments on these and other related topics (see Srivastava and Karlsson [2,pp. 350-351], Srivastava [3,4]). Our main objective in this survey-cum-expository article is based chiefly upon the fact that the recent and future usages of the classical q-calculus and the fractional q-calculus in geometric function theory of complex analysis have the potential to encourage and motivate significant further researches on many of these and other related subjects. Jackson [5,6] was the first that gave some application of q -calculus and introduced the q-analogue of derivative and integral operator (see also [7,8]), we apply the concept of q -convolution in order to introduce and study the general Taylor-Maclaurin coefficient estimates for functions belonging to a new class of normalized analytic in the open unit disk, which we have defined here.
Let A denote the class of analytic functions of the form
f(z):=z+∞∑m=2amzm,z∈Δ:={z∈C:|z|<1} | (1.1) |
and let S⊂A consisting on functions that are univalent in Δ. If the function h∈A is given by
h(z):=z+∞∑m=2bmzm,(z∈Δ). | (1.2) |
The Hadamard product (or convolution) of f and h, given by (1.1) and (1.2), respectively, is defined by
(f∗h)(z):=z+∞∑m=2ambmzm,z∈Δ. | (1.3) |
If f and F are analytic functions in Δ, we say that f is subordinate to F, written as f(z)≺F(z), if there exists a Schwarz function s, which is analytic in Δ, with s(0)=0, and |s(z)|<1 for all z∈Δ, such that f(z)=F(s(z)), z∈Δ. Furthermore, if the function F is univalent in Δ, then we have the following equivalence ([9,10])
f(z)≺F(z)⇔f(0)=F(0)andf(Δ)⊂F(Δ). |
The Koebe one-quarter theorem (see [11]) prove that the image of Δ under every univalent function f∈S contains the disk of radius 14. Therefore, every function f∈S has an inverse f−1 that satisfies
f(f−1(w))=w,(|w|<r0(f),r0(f)≥14), |
where
g(w)=f−1(w)=w−a2w2+(2a22−a3)w3−(5a32−5a2a3+a4)w4+⋯.=w+∞∑m=2Amwm |
A function f∈A is said to be bi-univalent in Δ if both f and f−1 are univalent in Δ. Let Σ represent the class of bi-univalent functions in Δ given by (1.1). The class of analytic bi-univalent functions was first familiarised by Lewin [12], where it was shown that |a2|<1.51. Brannan and Clunie [13] enhanced Lewin's result to |a2|<√2 and later Netanyahu [14] proved that |a2|<43.
Note that the functions
f1(z)=z1−z,f2(z)=12log1+z1−z,f3(z)=−log(1−z) |
with their corresponding inverses
f−11(w)=w1+w,f−12(w)=e2w−1e2w+1,f−13(w)=ew−1ew |
are elements of Σ (see [15,16]). For a brief history and exciting examples in the class Σ (see [17]). Brannan and Taha [18] (see also [16]) presented certain subclasses of the bi-univalent functions class Σ similar to the familiar subclasses S∗(α) and K(α) of starlike and convex functions of order α (0≤α<1), respectively (see [17,19,20]). Ensuing Brannan and Taha [18], a function f∈A is said to be in the class S∗Σ(α) of bi-starlike functions of order α (0<α≤1), if each of the following conditions are satisfied:
f∈Σ,with|argzf′(z)f(z)|<απ2(z∈Δ), |
and
|argwg′(w)g(w)|<απ2(w∈Δ), |
where the function g is the analytic extension of f−1 to Δ, given by
g(w)=w−a2w2+(2a22−a3)w3−(5a32−5a2a3+a4)w4+⋯(w∈Δ). | (1.4) |
A function f∈A is said to be in the class KΣ(α) of bi-convex functions of order α (0<α≤1), if each of the following conditions are satisfied:
f∈Σ,with|arg(1+zf′′(z)f′(z))|<απ2(z∈Δ), |
and
|arg(1+wg′′(w)g′(w))|<απ2(w∈Δ). |
The classes S∗Σ(α) and KΣ(α) of bi-starlike functions of order α and bi-convex functions of order α (0<α≤1), corresponding to the function classes S∗(α) and K(α), were also introduced analogously. For each of the function classes S∗Σ(α) and KΣ(α), they found non-sharp estimates on the first two Taylor-Maclaurin coefficients |a2| and |a3| ([16,18]).
The Faber polynomials introduced by Faber [21] play an important role in various areas of mathematical sciences, especially in Geometric Function Theory of Complex Analysis (see, for details, [22]). In 2013, Hamidi and Jahangiri [23,24,25] took a new approach to show that the initial coefficients of classes of bi- starlike functions e as well as provide an estimate for the general coefficients of such functions subject to a given gap series condition.Recently, their idea of application of Faber polynomials triggered a number of related publications by several authors (see, for example, [26,27,28] and also references cited threin) investigated some interesting and useful properties for analytic functions. Using the Faber polynomial expansion of functions f∈A has the form (1.1), the coefficients of its inverse map may be expressed as
g(w)=f−1(w)=w+∞∑m=21mK−mm−1(a2,a3,...)wm, | (1.5) |
where
K−mm−1(a2,a3,...)=(−m)!(−2m+1)!(m−1)!am−12+(−m)!(2(−m+1))!(m−3)!am−32a3+(−m)!(−2m+3)!(m−4)!am−42a4+(−m)!(2(−m+2))!(m−5)!am−52[a5+(−m+2)a23]+(−m)!(−2m+5)!(m−6)!am−62[a6+(−2m+5)a3a4]+∑i≥7am−i2Ui, | (1.6) |
such that Ui with 7≤i≤m is a homogeneous polynomial in the variables a2,a3,...,am, In particular, the first three terms of K−mm−1 are
K−21=−2a2,K−32=3(2a22−a3),K−43=−4(5a32−5a2a3+a4). |
In general, an expansion of K−nm (n∈N) is (see [29,30,31,32,33])
K−nm=nam+n(n−1)2D2m+n!3!(n−3)!D3m+...+n!m!(n−m)!Dmm, |
where Dnm=Dnm(a2,a3,...) and
Dpm(a1,a2,...am)=∞∑m=1p!i1!...im!ai11...aimm, |
while a1=1 and the sum is taken over all non-negative integers i1...im satisfying
i1+i2+...+im=pi1+2i2+...+mim=m. |
Evidently
Dmm(a1,a2,...am)=am1. |
Srivastava [1] made use of several operators of q-calculus and fractional q-calculus and recollecting the definition and representations. The q-shifted factorial is defined for κ,q∈C and n∈N0=N∪{0} as follows
(κ;q)m={1,m=0(1−κ)(1−κq)…(1−κqk−1),m∈N. |
By using the q-Gamma function Γq(z), we get
(qκ;q)m=(1−q)m Γq(κ+m)Γq(κ)(m∈N0), |
where (see [34])
Γq(z)=(1−q)1−z(q;q)∞(qz;q)∞(|q|<1). |
Also, we note that
(κ;q)∞=∞∏m=0(1−κqm)(|q|<1), |
and, the q-Gamma function Γq(z) is known
Γq(z+1)=[z]q Γq(z), |
where [m]q symbolizes the basic q-number defined as follows
[m]q:={1−qm1−q,m∈C1+m−1∑j=1qj,m∈N. | (1.7) |
Using the definition formula (1.7) we have the next two products:
(i) For any non-negative integer m, the q-shifted factorial is given by
[m]q!:={1,ifm=0,m∏n=1[n]q, ifm∈N. |
(ii) For any positive number r, the q-generalized Pochhammer symbol is defined by
[r]q,m:={1,ifm=0,r+m−1∏n=r[n]q,ifm∈N. |
It is known in terms of the classical (Euler's) Gamma function Γ(z), that
Γq(z)→Γ(z) asq→1−. |
Also, we observe that
limq→1−{(qκ;q)m(1−q)m}=(κ)m, |
where (κ)m is the familiar Pochhammer symbol defined by
(κ)m={1,ifm=0,κ(κ+1)...(κ+m−1),ifm∈N. |
For 0<q<1, the q-derivative operator (or, equivalently, the q- difference operator) El-Deeb et al. [35] defined Dq for f∗h given by (1.3) is defined by (see [5,6])
Dq(f∗h)(z):=Dq(z+∞∑m=2ambmzm)=(f∗h)(z)−(f∗h)(qz)z(1−q)=1+∞∑m=2[m]qambmzm−1(z∈Δ), |
where, as in the definition (1.7)
[m]q:={1−qm1−q=1+m−1∑j=1qj (m∈N),0 (m=0). | (1.8) |
For κ>−1 and 0<q<1, El-Deeb et al. [35] (see also) defined the linear operator Hκ,qh:A→A by
Hκ,qhf(z)∗Mq,κ+1(z)=zDq(f∗h)(z)(z∈Δ), |
where the function Mq,κ+1 is given by
Mq,κ+1(z):=z+∞∑m=2[κ+1]q,m−1[m−1]q!zm(z∈Δ). |
A simple computation shows that
Hκ,qhf(z):=z+∞∑m=2[m]q![κ+1]q,m−1ambm zm(κ>−1,0<q<1, z∈Δ). | (1.9) |
From the definition relation (1.9), we can easily verify that the next relations hold for all f∈A:
(i) [κ+1]qHκ,qhf(z)=[κ]qHκ+1,qhf(z)+qκz Dq(Hκ+1,qhf(z))(z∈Δ);(ii)Iκhf(z):=limq→1−Hκ,qhf(z)=z+∞∑m=2m!(κ+1)m−1ambmzm(z∈Δ). | (1.10) |
Remark 1. Taking precise cases for the coefficients bm we attain the next special cases for the operator Hκ,qh:
(ⅰ) For bm=1, we obtain the operator Iκq defined by Srivastava [32] and Arif et al. [36] as follows
Iκqf(z):=z+∞∑m=2[m]q![κ+1]q,m−1amzm(κ>−1,0<q<1, z∈Δ); | (1.11) |
(ⅱ) For bm=(−1)m−1Γ(υ+1)4m−1(m−1)!Γ(m+υ), υ>0, we obtain the operator Nκυ,q defined by El-Deeb and Bulboacă [37] and El-Deeb [38] as follows
Nκυ,qf(z):=z+∞∑m=2(−1)m−1Γ(υ+1)4m−1(m−1)!Γ(m+υ)⋅[m]q![κ+1]q,m−1amzm=z+∞∑m=2[m]q![κ+1]q,m−1ψmamzm(υ>0,κ>−1,0<q<1, z∈Δ), | (1.12) |
where
ψm:=(−1)m−1Γ(υ+1)4m−1(m−1)!Γ(m+υ); | (1.13) |
(ⅲ) For bm=(n+1n+m)α, α>0, n≥0, we obtain the operator Mκ,αn,q defined by El-Deeb and Bulboacă [39] and Srivastava and El-Deeb [40] as follows
Mκ,αn,qf(z):=z+∞∑m=2(n+1n+m)α⋅[m]q![κ+1]q,m−1amzm(z∈Δ); | (1.14) |
(ⅳ) For bm=ρm−1(m−1)!e−ρ, ρ>0, we obtain the q-analogue of Poisson operator defined by El-Deeb et al. [35] (see [41]) as follows
Iκ,ρqf(z):=z+∞∑m=2ρm−1(m−1)!e−ρ⋅[m]q![κ+1]q,m−1amzm(z∈Δ). | (1.15) |
(ⅴ) For bm=[1+ℓ+μ(m−1)1+ℓ]n, n∈Z, ℓ≥0, μ≥0, we obtain the q-analogue of Prajapat operator defined by El-Deeb et al. [35] (see also [42]) as follows
Jκ,nq,ℓ,μf(z):=z+∞∑m=2[1+ℓ+μ(m−1)1+ℓ]n⋅[m,q]![κ+1,q]m−1amzm(z∈Δ); | (1.16) |
(ⅵ) For bm=(n+m−2m−1)θm−1(1−θ)n n∈N, 0≤θ≤1, we obtain the q-analogue of the Pascal distribution operator defined by Srivastava and El-Deeb [28] (see also [35,43,44]) as follows
⊖κ,nq,θf(z):=z+∞∑m=2(n+m−2m−1)θm−1(1−θ)n⋅[m,q]![κ+1,q]m−1amzm(z∈Δ). | (1.17) |
The purpose of the paper is to present a new subclass of functions Lq,κΣ(η;h;Φ) of the class Σ, that generalize the previous defined classes. This subclass is defined with the aid of a general Hκ,qh linear operator defined by convolution products composed with the aid of q-derivative operator. This new class extend and generalize many preceding operators as it was presented in Remark 1, and the main goal of the paper is find estimates on the coefficients |a2|, |a3|, and for the Fekete-Szegö functional for functions in these new subclasses. These classes will be introduced by using the subordination and the results are obtained by employing the techniques used earlier by Srivastava et al. [16]. This last work represents one of the most important study of the bi-univalent functions, and inspired many investigations in this area including the present paper, while many other recent papers deals with problems initiated in this work, like [33,44,45,46,47,48], and many others. Inspired by the work of Silverman and Silvia [49] (also see[50]) and recent study by Srivastava et al [51], in this article, we define the following new subclass of bi-univalent functions Mq,κΣ(ϖ,ϑ,h) as follows:
Definition 1. Let ϖ∈(−π,π] and let the function f∈Σ be of the form (1.1) and h is given by (1.2), the function f is said to be in the class Mq,κΣ(ϖ,ϑ,h) if the following conditions are satisfied:
ℜ((Hκ,qhf(z))′+(1+eiϖ)2z(Hκ,qhf(z))′′)>ϑ, | (1.18) |
and
ℜ((Hκ,qhg(w))′+(1+eiϖ)2w(Hκ,qhg(w))′′)>ϑ | (1.19) |
with κ>−1, 0<q<1, 0≤ϑ<1 and z,w∈Δ, where the function g is the analytic extension of f−1 to Δ, and is given by (1.4).
Definition 2. Let ϖ=0 and let the function f∈Σ be of the form (1.1) and h is given by (1.2), the function f is said to be in the class Mq,κΣ(ϑ,h) if the following conditions are satisfied:
ℜ((Hκ,qhf(z))′+z(Hκ,qhf(z))′′)>ϑ, | (1.20) |
and
ℜ((Hκ,qhg(w))′+w(Hκ,qhg(w))′′)>ϑ | (1.21) |
with κ>−1, 0<q<1, 0≤ϑ<1 and z,w∈Δ, where the function g is the analytic extension of f−1 to Δ, and is given by (1.4).
Definition 3. Let ϖ=π and let the function f∈Σ be of the form (1.1) and h is given by (1.2), the function f is said to be in the class HMq,κΣ(ϑ,h) if the following conditions are satisfied:
ℜ((Hκ,qhf(z))′)>ϑandℜ((Hκ,qhg(w))′)>ϑ | (1.22) |
with κ>−1, 0<q<1, 0≤ϑ<1 and z,w∈Δ, where the function g is the analytic extension of f−1 to Δ, and is given by (1.4).
Remark 2. (ⅰ) Putting q→1− we obtain that limq→1−Mq,κΣ(ϖ,ϑ;h)=:GκΣ(ϖ,ϑ;h), where GκΣ(ϖ,ϑ;h) represents the functions f∈Σ that satisfy (1.18) and (1.19) for Hκ,qh replaced with Iκh (1.10).
(ⅱ) Fixing bm=(−1)m−1Γ(υ+1)4m−1(m−1)!Γ(m+υ), υ>0, we obtain the class Bq,κΣ(ϖ,ϑ,υ), that represents the functions f∈Σ that satisfy (1.18) and (1.19) for Hκ,qh replaced with Nκυ,q (1.12).
(ⅲ) Taking bm=(n+1n+m)α, α>0, n≥0, we obtain the class Lq,κΣ(ϖ,ϑ,n,α), that represents the functions f∈Σ that satisfy (1.18) and (1.19) for Hκ,qh replaced with Mκ,αn,q (1.14).
(ⅳ) Fixing bm=ρm−1(m−1)!e−ρ, ρ>0, we obtain the class Mq,κΣ(ϖ,ϑ,ρ), that represents the functions f∈Σ that satisfy (1.18) and (1.19) for Hκ,qh replaced with Iκ,ρq (1.15).
(ⅴ) Choosing bm=[1+ℓ+μ(m−1)1+ℓ]n, n∈Z, ℓ≥0, μ≥0, we obtain the class Mq,κΣ(ϖ,ϑ,n,ℓ,μ), that represents the functions f∈Σ that satisfy (1.18) and (1.19) for Hκ,qh replaced with Jκ,nq,ℓ,μ (1.16).
Throughout this paper, we assume that
ϖ∈(−π;π],κ>−1,0≤ϑ<1,0<q<1. |
Recall the following Lemma which will be needed to prove our results.
Lemma 1. (Caratheodory Lemma [11]) If ϕ∈P and ϕ(z)=1+∑∞n=1cnzn then |cn|≤2 for each n, this inequality is sharp for all n where P is the family of all functions ϕ analytic and having positive real part in Δ with ϕ(0)=1.
We firstly introduce a bound for the general coefficients of functions belong to the class Mq,κΣ(ϖ,ϑ;h).
Theorem 2. Let the function f given by (1.1) belongs to the class Mq,κΣ(ϖ,ϑ;h). If ak=0 for 2≤k≤m−1, then
|am|≤4(1−ϑ)[κ+1,q]m−1m|2+(1+eiϖ)(m−1)| [m,q]!bm. |
Proof. If f∈Mq,κΣ(ϖ,ϑ;h), from (1.18), (1.19), we have
((Hκ,qhf(z))′+(1+eiϖ)2z(Hκ,qhf(z))′′)=1+∞∑m=2m2[2+(1+eiϖ)(m−1)][m,q]![κ+1,q]m−1bmamzm−1(z∈Δ), | (2.1) |
and
((Hκ,qhg(w))′+(1+eiϖ)2z(Hκ,qhg(w))′′)=1+∞∑m=2m2[2+(1+eiϖ)(m−1)][m,q]![κ+1,q]m−1bm Amwm−1 |
=1+∞∑m=2m2[2+(1+eiϖ)(m−1)][m,q]![κ+1,q]m−1bm 1mK−mm−1(a2,...,am)wm−1(w∈Δ). | (2.2) |
Since
f∈Mq,κΣ(ϖ,ϑ;h) and g=f−1∈Mq,κΣ(γ,η,ϑ;h), |
we know that there are two positive real part functions:
U(z)=1+∞∑m=1cmzm, |
and
V(w)=1+∞∑m=1dmwm, |
where
ℜ(U(z))>0and ℜ(V(w))>0(z,w∈Δ), |
so that
(Hκ,qhf(z))′+(1+eiθ)2z(Hκ,qhf(z))′′=ϑ+(1−ϑ)U(z) |
=1+(1−ϑ)∞∑m=1cmzm, | (2.3) |
and
(Hκ,qhg(w))′+(1+eiθ)2z(Hκ,qhg(w))′′=ϑ+(1−ϑ)V(w) |
=1+(1−ϑ)∞∑m=1dmwm. | (2.4) |
Using (2.1) and comparing the corresponding coefficients in (2.3), we obtain
m2[2+(1+eiϖ)(m−1)][m,q]![κ+1,q]m−1bmam=(1−ϑ)cm−1, | (2.5) |
and similarly, by using (2.2) in the equality (2.4), we have
m2[2+(1+eiϖ)(m−1)][m,q]![κ+1,q]m−1bm1mK−mm−1(a2,a3,...am)=(1−ϑ)dm−1, | (2.6) |
under the assumption ak=0 for 0≤k≤m−1, we obtain Am=−am and so
m2[2+(1+eiϖ)(m−1)][m,q]![κ+1,q]m−1bmam=(1−ϑ)cm−1, | (2.7) |
and
−m2[2+(1+eiϖ)(m−1)][m,q]![κ+1,q]m−1bmam=(1−ϑ)dm−1, | (2.8) |
Taking the absolute values of (2.7) and (2.8), we conclude that
|am|=|2(1−ϑ)[κ+1,q]m−1cm−1m[2+(1+eiϖ)(m−1)] [m,q]!bm|=|−2(1−ϑ)[κ+1,q]m−1dm−1m[2+(1+eiϖ)(m−1)] [m,q]!bm|. |
Applying the Caratheodory Lemma 1, we obtain
|am|≤4(1−ϑ)[κ+1,q]m−1m|2+(1+eiϖ)(m−1)| [m,q]!bm, |
which completes the proof of Theorem.
Theorem 3. Let the function f given by (1.1) belongs to the class Mq,κΣ(ϖ,ϑ;h), then
|a2|≤{2(1−ϑ)[κ+1,q]|3+eiϖ|[2,q]!b2,0≤ϑ<1−|3+eiϖ|2 ([2,q]!)2[κ+2,q]b223|2+eiϖ| [3,q]![κ+1,q]b3√2(1−ϑ)[κ+1,q]23|2+eiϖ| [3,q]!b3,1−|3+eiϖ|2 ([2,q]!)2[κ+2,q]b223|2+eiϖ| [3,q]![κ+1,q]b3≤ϑ<1, | (2.9) |
|a3|≤2(1−ϑ)[κ+1,q]23|2+eiϖ|[3,q]!b3, | (2.10) |
and
|a3−2a22|≤2(1−ϑ)[κ+1,q]23|2+eiϖ| [3,q]!b3. | (2.11) |
Proof. Fixing m=2 and m=3 in (2.5), (2.6), we have
(3+eiϖ) [2,q]![κ+1,q]b2a2=(1−ϑ)c1, | (2.12) |
3(2+eiϖ) [3,q]![κ+1,q]2b3a3=(1−ϑ)c2, | (2.13) |
−(3+eiϖ) [2,q]![κ+1,q]b2a2=(1−ϑ)d1, | (2.14) |
and
−3(2+eiϖ) [3,q]![κ+1,q]2b3(2a22−a3)=(1−ϑ)d2. | (2.15) |
From (2.12) and (2.14), by using the Caratheodory Lemma1, we obtain
|a2|=(1−ϑ)[κ+1,q]|c1||3+eiϖ|[2,q]!b2=(1−ϑ)[κ+1,q]|d1||3+eiϖ|[2,q]!b2≤2(1−ϑ)[κ+1,q]|3+eiϖ|[2,q]!b2. | (2.16) |
Also, from (2.13) and (2.15), we have
6(2+eiϖ) [3,q]![κ+1,q]2b3a22=(1−ϑ)(c2+d2), |
a22=(1−ϑ)[κ+1,q]26(2+eiϖ)[3,q]!b3(c2+d2), | (2.17) |
and by using the Caratheodory Lemma 1, we obtain
|a2|≤√2(1−ϑ)[κ+1,q]23|2+eiϖ| [3,q]!b3. | (2.18) |
From (2.16) and (2.18), we obtain the desired estimate on the coefficient as asserted in (2.9).
To find the bound on the coefficient |a3|, we subtract (2.15) from (2.13). we get
6(2+eiϖ) [3,q]![κ+1,q]2b3(a3−a22)=(1−ϑ)(c2−d2), |
or
a3=a22+(1−ϑ)(c2−d2)[κ+1,q]26(2+eiϖ)[3,q]!b3, | (2.19) |
substituting the value of a22 from (2.12) into (2.19), we obtain
a3=(1−ϑ)2[κ+1,q]2c21(3+eiϖ)2([2,q]!)2b22+(1−ϑ)(c2−d2)[κ+1,q]26(2+eiϖ)[3,q]!b3. |
Using the Caratheodory Lemma 1, we find that
|a3|≤4(1−ϑ)2[κ+1,q]2|3+eiϖ|2([2,q]!)2b22+2(1−ϑ)[κ+1,q]23|2+eiϖ|[3,q]!b3, | (2.20) |
and from (2.13), we have
a3=(1−ϑ)[κ+1,q]2 c23(2+eiϖ)[3,q]!b3. |
Appling the Caratheodory Lemma 1, we obtain
|a3|≤2(1−ϑ)[κ+1,q]23|2+eiϖ|[3,q]!b3. | (2.21) |
Combining (2.20) and (2.21), we have the desired estimate on the coefficient |a3| as asserted in (2.10).
Finally, from (2.15), we deduce that
|a3−2a22|≤(1−ϑ)[κ+1,q]2|d2|3|2+eiϖ| [3,q]!b3=2(1−ϑ)[κ+1,q]23|2+eiϖ| [3,q]!b3. |
Thus the proof of Theorem 3 was completed.
Fekete and Szegö [52] introduced the generalized functional |a3−ℵa22|, where ℵ is some real number. Due to Zaprawa [53], (also see [54]) in the following theorem we determine the Fekete-Szegö functional for f∈Mq,κΣ(ϖ,ϑ;h).
Theorem 4. Let the function f given by (1.1) belongs to the class Mq,κΣ(ϖ,ϑ;h) and ℵ∈R. Then we have
|a3−ℵa22|≤((1−ϑ)[κ+1,q]23|2+eiϖ|[3,q]!b3){|2−ℵ|+|ℵ|}. |
Proof. From (2.17) and (2.19)we obtain
a3−ℵa22=(1−ℵ)(1−ϑ)[κ+1,q]26(2+eiϖ)[3,q]!b3(c2+d2)+(1−ϑ)[κ+1,q]26(2+eiϖ)[3,q]!b3(c2−d2),=((1−ϑ)[κ+1,q]26(2+eiϖ)[3,q]!b3){[(1−ℵ)+1]c2+[(1−ℵ)−1]d2}. |
So we have
a3−ℵa22=((1−ϑ)[κ+1,q]26(2+eiϖ)[3,q]!b3){(2−ℵ)c2+(−ℵ)d2}. | (3.1) |
Then, by taking modulus of (3.1), we conclude that
|a3−ℵa22|≤((1−ϑ)[κ+1,q]23|2+eiϖ|[3,q]!b3){|2−ℵ|+|ℵ|} |
Taking ℵ=1, we have the following result.
|a3−a22|≤2(1−ϑ)[κ+1,q]23|2+eiϖ|[3,q]!b3. |
In the current paper, we mainly get upper bounds of the initial Taylors coefficients of bi-univalent functions related with q− calculus operator. By fixing bm as demonstrated in Remark 1, one can effortlessly deduce results correspondents to Theorems 2 and 3 associated with various operators listed in Remark 1. Further allowing q→1− as itemized in Remark 2 we can outspread the results for new subclasses stated in Remark 2. Moreover by fixing ϖ=0 and ϖ=π in Theorems 2 and 3, we can easily state the results for f∈Mq,κΣ(ϑ;h) and f∈HMq,κΣ(ϑ;h). Further by suitably fixing the parameters in Theorem 4, we can deduce Fekete-Szegö functional for these function classes. By using the subordination technique, we can extend the study by defining a new class
[(Hκ,qhf(z))′+(1+eiϖ2)z(Hκ,qhf(z))′′]≺Ψ(z) |
where Ψ(z) the function Ψ is an analytic univalent function such that ℜ(Ψ)>0inΔ with Ψ(0)=1,Ψ′(0)>0 and Ψ maps Δ onto a region starlike with respect to 1 and symmetric with respect to the real axis and is given by Ψ(z)=z+B1z+B2z2+B3z3+⋯,(B1>0). Also, motivating further researches on the subject-matter of this, we have chosen to draw the attention of the interested readers toward a considerably large number of related recent publications (see, for example, [1,2,4]). and developments in the area of mathematical analysis. In conclusion, we choose to reiterate an important observation, which was presented in the recently-published review-cum-expository review article by Srivastava ([1], p. 340), who pointed out the fact that the results for the above-mentioned or new q− analogues can easily (and possibly trivially) be translated into the corresponding results for the so-called (p;q)−analogues(with 0<|q|<p≤1)by applying some obvious parametric and argument variations with the additional parameter p being redundant.
The researcher(s) would like to thank the Deanship of Scientific Research, Qassim University for funding the publication of this project.The authors are grateful to the reviewers for their valuable remarks, comments, and advices that help us to improve the quality of the paper.
The authors declare that they have no competing interests.
[1] |
G. M. Cordeiro, E. M. Ortega, B. V. Popović, R. R. Pescim, The Lomax generator of distributions: Properties, minification process and regression model, Appl. Math. Comput., 247 (2014), 465–486. https://doi.org/10.1016/j.amc.2014.09.004 doi: 10.1016/j.amc.2014.09.004
![]() |
[2] |
V. S. Vaidyanathan, A. S. Varghese, Morgenstern type bivariate lindley distribution, Stat. Optim. Inf. Comput., 4 (2016), 132–146. https://doi.org/10.19139/soic.v4i2.183 doi: 10.19139/soic.v4i2.183
![]() |
[3] |
L. Baharith, H. Alzahrani, New bivariate Pareto type Ⅱ models, Entropy, 21 (2019), 473. https://doi.org/10.3390/e21050473 doi: 10.3390/e21050473
![]() |
[4] |
M. V. Peres, R. P. Oliveira, J. A. Achcar, E. Z. Martinez, The Bivariate defective Gompertz distribution based on Clayton Copula with applications to medical data, Aust. J. Stat., 51 (2022), 144–168. https://doi.org/10.17713/ajs.v51i2.1285 doi: 10.17713/ajs.v51i2.1285
![]() |
[5] | E. M. Almetwally, H. Z. Muhammed, On a bivariate Frechet distribution, J. Stat. Appl. Proba., 9 (2020), 1–21. |
[6] |
M. V. Perres, J. A. Achcar, E. Z. Martinez, Bivariate lifetime models in presence of cure fraction: A comparative study with many different copula functions, Heliyon, 6 (2020), e03961. https://doi.org/10.1016/j.heliyon.2020.e03961 doi: 10.1016/j.heliyon.2020.e03961
![]() |
[7] |
J. Zhao, H. Faqiri, Z. Ahmad, W. Emam, M. Yusuf, A. M. Sharawy, The Lomax-Claim model: Bivariate extension and applications to financial data, Complexity, 2021, 1–17. https://doi.org/10.1155/2021/9993611 doi: 10.1155/2021/9993611
![]() |
[8] |
H. H. Ahmad, E. M. Almetwally, D. A. Ramadan, Investigating the relationship between processor and memory reliability in data science: A bivariate model approach, Mathematics, 11 (2023), 2142. https://doi.org/10.3390/math11092142 doi: 10.3390/math11092142
![]() |
[9] |
M. E. Qura, A. Fayomi, M. Kilai, E. M. Almetwally, Bivariate power Lomax distribution with medical applications, Plos One, 18 (2023), e0282581. https://doi.org/10.1371/journal.pone.0282581 doi: 10.1371/journal.pone.0282581
![]() |
[10] |
E. S. A. El-Sherpieny, E. M. Almetwally, U. Z. Muhammed, Bivariate Weibull-G family based on copula function: Properties, Bayesian and non-Bayesian estimation and applications, Stat. Optim. Inf. Comput., 10 (2022), 678–709. https://doi.org/10.19139/soic-2310-5070-1129 doi: 10.19139/soic-2310-5070-1129
![]() |
[11] |
H. Z. Muhammed, Bivariate inverse Weibull distribution, J. Stat. Comput. Simul., 86 (2016), 2335–2345. https://doi.org/10.1080/00949655.2015.1110585 doi: 10.1080/00949655.2015.1110585
![]() |
[12] |
M. S. Eliwa, M. El-Morshedy, Bivariate Gumbel-G family of distributions: Statistical properties, Bayesian and non-Bayesian estimation with application, Ann. Data Sci., 6 (2019), 39–60. https://doi.org/10.1007/s40745-018-00190-4 doi: 10.1007/s40745-018-00190-4
![]() |
[13] |
R. M. Alotaibi, H. R. Rezk, I. Ghosh, S. Dey, Bivariate exponentiated half logistic distribution: Properties and application, Commun. Stat.-Theor. M., 50 (2021), 6099–6121. https://doi.org/10.1080/03610926.2020.1739310 doi: 10.1080/03610926.2020.1739310
![]() |
[14] | E. S. A. El-Sherpieny, H. Z. Muhammed, E. M. Almetwally, Accelerated life testing for bivariate distributions based on progressive censored samples with random removal, J. Stat. Appl. Probab., 11 (2022), 203–223. |
[15] | A. Sklar, Fonctions de répartition à n dimensions et leurs marges, Publications de l'Institut de statistique de l'Université de Paris, 8 (1959), 229–231. |
[16] | R. B. Nelsen, An introduction to copulas, 2 Eds., Springer Science Business Media, 2006. |
[17] | H. Joe, Multivariate models and dependence concepts, 2 Eds., New York: Chapman and Hall, 1997. https://doi.org/10.1201/9780367803896 |
[18] |
E. J. Gumbel, Bivariate exponential distributions, J. Am. Stat. Assoc., 55 (1960), 698–707. https://doi.org/10.1080/01621459.1960.10483368 doi: 10.1080/01621459.1960.10483368
![]() |
[19] |
N. Sreelakshmi, An introduction to copula-based bivariate reliability concepts, Commun. Stat.- Theor. M., 47 (2018), 996–1012. https://doi.org/10.1080/03610926.2017.1316396 doi: 10.1080/03610926.2017.1316396
![]() |
[20] |
I. W. Burr, Cumulative frequency functions, Ann. Math. Stat., 13 (1942), 215–232. https://doi.org/10.1214/aoms/1177731607 doi: 10.1214/aoms/1177731607
![]() |
[21] |
L. J. Bain, Analysis for the linear failure rate life-testing distribution, Technometrics, 16 (1974), 551–559. https://doi.org/10.1080/00401706.1974.10489237 doi: 10.1080/00401706.1974.10489237
![]() |
[22] |
K. S. Lomax, Business failures: Another example of the analysis of failure, J. Am. Stat. Assoc., 49 (1954), 847–852. https://doi.org/10.1080/01621459.1954.10501239 doi: 10.1080/01621459.1954.10501239
![]() |
[23] | I. S. Gradshteyn, I. M. Ryzhik, Table of integrals, series, and products, 7 Eds., San Diego: Academic Press, 2007. |
[24] |
A. Basu, Bivariate failure rate, J. Am. Stat. Assoc., 66 (1971), 103–104. https://doi.org/10.1080/01621459.1971.10482228 doi: 10.1080/01621459.1971.10482228
![]() |
[25] |
N. L. Johnson, S. Kotz, A vector multivariate hazard rate, J. Multivariate Anal., 5 (1975), 53–66. https://doi.org/10.1016/0047-259X(75)90055-X doi: 10.1016/0047-259X(75)90055-X
![]() |
[26] |
E. L. Lehmann, Some concepts of dependence, Ann. Math. Statist., 37 (1966), 1137–1153. https://doi.org/10.1214/aoms/1177699260 doi: 10.1214/aoms/1177699260
![]() |
[27] |
W. Holland, Y. J. Wang, Dependence function for continuous bivariate densities, Commun. Stat.- Theor. M., 16 (1987), 863–876. https://doi.org/10.1080/03610928708829408 doi: 10.1080/03610928708829408
![]() |
[28] | N. Balakrishnan, C. D. Lai, Continuous bivariate distributions, 2 Eds., New York: Springer Science Business Media, 2009. |
[29] |
D. G. Clayton, A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence, Biometrika, 65 (1978), 141–151. https://doi.org/10.1093/biomet/65.1.141 doi: 10.1093/biomet/65.1.141
![]() |
[30] |
D. Oakes, Bivariate survival models induced by frailties, J. Am. Stat. Assoc., 84 (1989), 487–493. https://doi.org/10.1080/01621459.1989.10478795 doi: 10.1080/01621459.1989.10478795
![]() |
[31] |
J. E. Anderson, T. A. Louis, N. V. Holm, B. Harvald, Time-dependent association measures for bivariate survival distributions, J. Am. Stat. Assoc., 87 (1992), 641–650. https://doi.org/10.1080/01621459.1992.10475263 doi: 10.1080/01621459.1992.10475263
![]() |
[32] |
R. B. Nelsen, Concordance and Gini's measure of association, J. Nonparametr. Stat., 9 (1998), 227–238. https://doi.org/10.1080/10485259808832744 doi: 10.1080/10485259808832744
![]() |
[33] |
B. V. Popović, M. M. Ristić, A. İ. Genç, Dependence properties of multivariate distributions with proportional hazard rate marginals, Appl. Math. Model., 77 (2020), 182–198. https://doi.org/10.1016/j.apm.2019.07.030 doi: 10.1016/j.apm.2019.07.030
![]() |
[34] |
H. Dette, K. F. Siburg, P. A. Stoimenov, A copula-based non-parametric measure of regression dependence, Scand. J. Stat., 40 (2013), 21–41. https://doi.org/10.1111/j.1467-9469.2011.00767.x doi: 10.1111/j.1467-9469.2011.00767.x
![]() |
[35] |
N. L. Johnson, S. Kotz, On some generalized Farlie-Gumbel-Morgenstern distributions, Commun. Stat., 4 (1975), 415–427. https://doi.org/10.1080/03610917508548400 doi: 10.1080/03610917508548400
![]() |
[36] | A. K. Suzuki, F. Louzada-Neto, V. G. Cancho, G. D. Barriga, The FGM bivariate lifetime copula model: A bayesian approach, Adv. Appl. Stat., 21 (2011), 55–76. |
[37] |
F. Louzada, A. K. Suzuki, V. G. Cancho, The FGM long-term bivariate survival copula model: Modeling, Bayesian estimation, and case influence diagnostics, Commun. Stat.-Theor. M., 42 (2013), 673–691. https://doi.org/10.1080/03610926.2012.725147 doi: 10.1080/03610926.2012.725147
![]() |
[38] |
M. H. Chen, Q. M. Shao, Monte Carlo estimation of Bayesian credible and HPD intervals, J. Comput. Graph. Stat., 8 (1999), 69–92. https://doi.org/10.1080/10618600.1999.10474802 doi: 10.1080/10618600.1999.10474802
![]() |
[39] |
M. K. Hassan, C. Chesneau, Bivariate generalized half-logistic distribution: Properties and its application in household financial affordability in KSA, Math. Comput. Appl., 27 (2022), 72. https://doi.org/10.3390/mca27040072 doi: 10.3390/mca27040072
![]() |
[40] | G. Grover, A. Sabharwal, J. Mittal, Application of multivariate and bivariate normal distributions to estimate duration of diabetes, Int. J. Stat. Appl., 4 (2014), 46–57. |
[41] |
R. P. Oliveira, J. A. Achcar, J. Mazucheli, W. Bertoli, A new class of bivariate Lindley distributions based on stress and shock models and some of their reliability properties, Reliab. Eng. Syst., 211 (2021), 107528. https://doi.org/10.1016/j.ress.2021.107528 doi: 10.1016/j.ress.2021.107528
![]() |
[42] |
C. A. McGilchrist, C. W. Aisbett, Regression with frailty in survival analysis, Biometrics, 47 (1991), 461–466. https://doi.org/10.2307/2532138 doi: 10.2307/2532138
![]() |
1. | Nikhil Pachauri, Velamuri Suresh, MVV Prasad Kantipudi, Reem Alkanhel, Hanaa A. Abdallah, Multi-Drug Scheduling for Chemotherapy Using Fractional Order Internal Model Controller, 2023, 11, 2227-7390, 1779, 10.3390/math11081779 | |
2. | Ahlem Benzahi, Nadjet Abada, Nouria Arar, Sahar Ahmed Idris, Mohammed S. Abdo, Wasfi Shatanawi, Caputo-Fabrizio type fractional differential equations with non-instantaneous impulses: Existence and stability results, 2024, 87, 11100168, 186, 10.1016/j.aej.2023.12.036 | |
3. | H. Çerdik Yaslan, Pell polynomial solution of the fractional differential equations in the Caputo–Fabrizio sense, 2024, 0019-5588, 10.1007/s13226-024-00684-3 | |
4. | Hassan Kamil Jassim, Mohammed Abdulshareef Hussein, Mohamed R. Ali, 2023, 2899, 0094-243X, 060008, 10.1063/5.0157148 | |
5. | Amine Moustafid, Cancer Modeling by Fractional Derivative Equation and Chemotherapy Stabilizing, 2024, 7, 2651-4001, 125, 10.33434/cams.1486049 | |
6. | Hassan Kamil Jassim, Ali Thamir Salman, Hijaz Ahmad, Muslim Yusif Zayir, Ali Hussein Shuaa, 2023, 2899, 0094-243X, 060007, 10.1063/5.0157146 | |
7. | Boyu Liu, Wenyan Wang, An efficient numerical scheme in reproducing kernel space for space fractional partial differential equations, 2024, 9, 2473-6988, 33286, 10.3934/math.20241588 | |
8. | Emadidin Gahalla Mohmed Elmahdi, Yang Yi, Jianfei Huang, Two linearized difference schemes on graded meshes for the time-space fractional nonlinear diffusion-wave equation with an initial singularity, 2025, 100, 0031-8949, 015215, 10.1088/1402-4896/ad95c4 | |
9. | Jocelyn Sabatier, Fractional Dynamical Behaviour Modelling Using Convolution Models with Non-Singular Rational Kernels: Some Extensions in the Complex Domain, 2025, 9, 2504-3110, 79, 10.3390/fractalfract9020079 | |
10. | Junseok Kim, A normalized Caputo–Fabrizio fractional diffusion equation, 2025, 10, 2473-6988, 6195, 10.3934/math.2025282 | |
11. | Barun Singh Katoch, Surjeet Singh Chauhan Gonder, 2025, 3283, 0094-243X, 040003, 10.1063/5.0265023 | |
12. | Manal Alqhtani, Lakhlifa Sadek, Khaled Mohammed Saad, The Mittag-Leffler–Caputo–Fabrizio Fractional Derivative and Its Numerical Approach, 2025, 17, 2073-8994, 800, 10.3390/sym17050800 |