Survival data with high dimensional covariates have been collected in medical studies and other fields. In this work, we propose a seamless L0 (SELO) penalized method for the accelerated failure time (AFT) model under the framework of high dimension. Specifically, we apply the SELO to do variable selection and estimation under this model. Under appropriate conditions, we show that the SELO selects a model whose dimension is comparable to the underlying model, and prove that the proposed procedure is asymptotically normal. Simulation results demonstrate that the SELO procedure outperforms other existing procedures. The real data analysis is considered as well which shows that SELO selects the variables more correctly.
Citation: Yin Xu, Ning Wang. Variable selection and estimation for accelerated failure time model via seamless-L0 penalty[J]. AIMS Mathematics, 2023, 8(1): 1195-1207. doi: 10.3934/math.2023060
[1] | Kanagaraj Muthuselvan, Baskar Sundaravadivoo, Kottakkaran Sooppy Nisar, Suliman Alsaeed . Discussion on iterative process of nonlocal controllability exploration for Hilfer neutral impulsive fractional integro-differential equation. AIMS Mathematics, 2023, 8(7): 16846-16863. doi: 10.3934/math.2023861 |
[2] | Ahmed Morsy, Kottakkaran Sooppy Nisar, Chokkalingam Ravichandran, Chandran Anusha . Sequential fractional order Neutral functional Integro differential equations on time scales with Caputo fractional operator over Banach spaces. AIMS Mathematics, 2023, 8(3): 5934-5949. doi: 10.3934/math.2023299 |
[3] | Mohammed A. Almalahi, Satish K. Panchal, Fahd Jarad, Mohammed S. Abdo, Kamal Shah, Thabet Abdeljawad . Qualitative analysis of a fuzzy Volterra-Fredholm integrodifferential equation with an Atangana-Baleanu fractional derivative. AIMS Mathematics, 2022, 7(9): 15994-16016. doi: 10.3934/math.2022876 |
[4] | Marimuthu Mohan Raja, Velusamy Vijayakumar, Anurag Shukla, Kottakkaran Sooppy Nisar, Wedad Albalawi, Abdel-Haleem Abdel-Aty . A new discussion concerning to exact controllability for fractional mixed Volterra-Fredholm integrodifferential equations of order r∈(1,2) with impulses. AIMS Mathematics, 2023, 8(5): 10802-10821. doi: 10.3934/math.2023548 |
[5] | Sivaranjani Ramasamy, Thangavelu Senthilprabu, Kulandhaivel Karthikeyan, Palanisamy Geetha, Saowaluck Chasreechai, Thanin Sitthiwirattham . Existence, uniqueness and controllability results of nonlinear neutral implicit ABC fractional integro-differential equations with delay and impulses. AIMS Mathematics, 2025, 10(2): 4326-4354. doi: 10.3934/math.2025200 |
[6] | Qi Wang, Chenxi Xie, Qianqian Deng, Yuting Hu . Controllability results of neutral Caputo fractional functional differential equations. AIMS Mathematics, 2023, 8(12): 30353-30373. doi: 10.3934/math.20231550 |
[7] | Rajesh Dhayal, Muslim Malik, Syed Abbas . Solvability and optimal controls of non-instantaneous impulsive stochastic neutral integro-differential equation driven by fractional Brownian motion. AIMS Mathematics, 2019, 4(3): 663-683. doi: 10.3934/math.2019.3.663 |
[8] | Yong-Ki Ma, Marimuthu Mohan Raja, Kottakkaran Sooppy Nisar, Anurag Shukla, Velusamy Vijayakumar . Results on controllability for Sobolev type fractional differential equations of order 1<r<2 with finite delay. AIMS Mathematics, 2022, 7(6): 10215-10233. doi: 10.3934/math.2022568 |
[9] | Hasanen A. Hammad, Mohammed E. Dafaalla, Kottakkaran Sooppy Nisar . A Grammian matrix and controllability study of fractional delay integro-differential Langevin systems. AIMS Mathematics, 2024, 9(6): 15469-15485. doi: 10.3934/math.2024748 |
[10] | H. H. G. Hashem, Hessah O. Alrashidi . Qualitative analysis of nonlinear implicit neutral differential equation of fractional order. AIMS Mathematics, 2021, 6(4): 3703-3719. doi: 10.3934/math.2021220 |
Survival data with high dimensional covariates have been collected in medical studies and other fields. In this work, we propose a seamless L0 (SELO) penalized method for the accelerated failure time (AFT) model under the framework of high dimension. Specifically, we apply the SELO to do variable selection and estimation under this model. Under appropriate conditions, we show that the SELO selects a model whose dimension is comparable to the underlying model, and prove that the proposed procedure is asymptotically normal. Simulation results demonstrate that the SELO procedure outperforms other existing procedures. The real data analysis is considered as well which shows that SELO selects the variables more correctly.
It was recognized that in 1922, Banach proved a "contraction mapping principle for fixed points (FPs)" in his Ph.D. dissertation; see also [1]. It is one of the most significant results in functional analysis and its applications in other branches of mathematics. Specifically, this principle is considered as the basic source of metric FP theory. The study of FP and common fixed point (CFP) results satisfying a certain metric contraction condition has received the attention of many authors; see, for instance [2,3,4,5,6,7,8,9,10].
Huang and Zhang [11] in 2007, introduced the notion of a cone metric space (CM-space) which generalized the notion of a metric space (M-space). They presented some basic properties and proved a cone Banach contraction theorem for FPs in terms of the interior points of the underlying cone. After the publication of this article, many researchers contributed their work to the problems on CM-spaces. Abbas and Jungck [12], Ilić and Rakocević [13] and Vetro [14] generalized the concept of Huang and Zhang [11] and proved some FP, CFP and coincidence point results on CM-spaces by using different types of contraction conditions. Abbas et al. [15], Abdeljawad et al. [16,17], Altun et al. [18], Janković et al. [19], Karapinar [20,21,22], Khamsi [23], Kumar and Rathee [24], and Rezapour and Hamlbarani [25] proved different contractive-type FP and CFP results on CM-spaces.
In 1969, Nadler [26] initially introduced the concept of multi-valued contraction mappings in the theory of FP by using the Hausdorff metric. He proved some multi-valued FP results on complete M-spaces. In other papers [28,29,30,31], the authors contributed their ideas to the theory of FP and established multi-valued contraction results in the context of M-spaces. In [32], Rezapour and Haghi proved FP results for multi-functions on CM-spaces. Later on, Klim and Wardowski [33] established some FP results for set-valued nonlinear contraction mappings on CM-spaces. After that, Latif and Shaddad [34] proved some FP results for multi-valued maps on CM-spaces. Cho and Bae [35] presented modified FP theorems for multi-valued mappings on CM-spaces. Meanwhile, Wardowski [36] proved some Nadler type contraction results for set-valued mappings on CM-spaces. Mehmood et al. [37,38], proved some multi-valued contraction results for FPs on CM-space and order CM-spaces with an application. In 2015, Fierro [39] established some FP theorems on topological vector spaces valued CM-spaces for set-valued mappings. Recently, Rehman et al. [40] proved some multi-valued contraction theorems for FPs and CFPs on H−CM-spaces.
In this paper, we study some new types of generalized multi-valued contraction results on complete CM-spaces. We prove some CFP theorems for a pair of multi-valued contraction mappings on CM-spaces with the condition of normality of the cone. We present an illustrative example to support our work. Further, we present an application of nonlinear integral equations to validate our work. This concept can be extended for different types of multi-valued contraction mappings in the context of M-spaces with the application of different types of integral equations and differential equations. This paper is organized as follows: in Section 2, we introduce the preliminary concepts related to our main work. In Section 3, we establish some CFP theorems for a pair of multi-valued contraction mappings on CM-spaces with an illustrative example. In Section 4, we present a supportive application of nonlinear integral equations to unify our main work. Finally, in Section 5, we present the conclusion of our work.
Definition 2.1. [11] Let E be a real Banach space. A subset P⊆E is called a cone if the following are satisfied:
(ⅰ) P is closed, nonempty and P≠{θ}, where θ is the zero element of E;
(ⅱ) If 0≤b1,b2<∞ and u1,u2∈P, then b1u1+b2u2∈P;
(ⅲ) P∩−P={θ}.
Given a cone P⊆E, define a partial ordering ≤ on E with respect to P by u1≤u2 if and only if u2−u1∈P. We shall write u1<u2 if u1≤u2 and u1≠u2 while u1≪u2, and if and only if u2−u1∈int(P), where int(P) denotes the interior of P. A nonempty cone P is called normal if there is K>1 such that ∀ u1,u2∈E, ‖u1‖≤K‖u2‖, whenever θ≤u1≤u2.
A cone P is known as regular if every non-decreasing sequence which is bounded from above is convergent, i.e., if {un} is a sequence such that for some v∈E, we have u1≤u2≤⋯≤v. Then there exists u∗∈E such that
limn→+∞‖un−u∗‖=0. |
Equivalently, a cone P is regular if and only if every non-increasing sequence which is bounded from below is convergent.
Throughout this paper, we assume that E is a real Banach space, P is a cone in E with int(P)≠∅ and ≤ is the partial ordering on E with respect to P.
Definition 2.2. [11] Let U be a nonempty set. Let δ: U×U→E be called a cone metric if the following hold
(ⅰ) δ(u1,u2)≥θ and δ(u1,u2)=θ⇔u1=u2;
(ⅱ) δ(u1,u2)=δ(u2,u1);
(ⅲ) δ(u1,u2)≤δ(u1,u3)+δ(u3,u2);
for all u1,u2,u3∈U. The a pair (U,δ) is called a CM-space.
Definition 2.3. [11] Let (U,δ) be a CM-space. Let υ∈U and {un} be a sequence in U. Then the following are true:
(ⅰ) {un} is said to be convergent to υ if for every ζ∈E with ζ≫θ, there is a positive integer N such that δ(un,υ)≪ζ for n≥N. We denote this by limn→+∞un=υ or un→υ as n→+∞.
(ⅱ) {un} is said to be a Cauchy sequence if for every ζ∈E with ζ≫θ, there is a positive integer N such that δ(un,um)≪ζ for m,n≥N.
(ⅲ) (U,δ) is called complete if every Cauchy sequence is convergent in U.
Lemma 2.4. [11] Let (U,δ) be a CM-space and P be a normal cone. Let {un} be a sequence in U and u,v∈U. Then the following are true:
(ⅰ) limn→+∞un=u⇔limn→+∞δ(un,u)=θ.
(ⅱ) {un} is a Cauchy sequence iff limm,n→+∞δ(un,um)=θ.
(ⅲ) If limn→+∞un=u and limn→+∞un=v, then u=v.
In what follows, B denotes (resp. B(U), CB(U)) the set of nonempty (resp. bounded, sequentially closed and bounded) subsets of (U,δ).
Let (U,δ) be a CM-space and we denote
s(u1)={u2∈E: u1≤u2} |
for u1∈E, and
s(x,B)=∪y∈B s(δ(x,y)) |
for x∈U and B∈B. For A,B∈B(U), we represent
s(A,B)=(∩x∈A s(x,B))⋂(∩y∈B s(y,A)). |
Lemma 2.5. [35] Let (U,δ) be a CM-space and P be a cone in Banach space E. Then the following are true:
(ⅰ) For all u1,u2∈E, if u1≤u2, then s(u2)⊆s(u1).
(ⅱ) For all u∈U and A∈B, if θ∈s(u,A), then u∈A.
(ⅲ) For all u1∈P and A,B∈B(U) and x∈A, if u1∈s(A,B), then u1∈s(x,B).
(ⅳ) If un∈E with un→θ, then for each ζ∈int(P) there exists N such that un≪ζ for all n>N.
Remark 2.6. [35] Let (U,δ) be a CM-space.
(ⅰ) If E=R and P=[0,+∞), then (U,δ) is an M-space. Moreover, for A,B∈CB(U), Hδ(A,B)=infs(A,B) is the Hausdorff distance induced by δ.
(ⅱ) s({x},{y})=s(δ(x,y)) for x,y∈U.
Definition 2.7. Let T: U→CB(U) be a multi-valued map. An element u0∈U is called an FP of T if u0∈Tu0.
Theorem 2.8. [26] Let (U,δ) be a complete M-space. Let T: U→CB(U) satisfy
Hδ(Tμ,Tν)≤ηδ(μ,ν), ∀ μ,ν∈U, | (2.1) |
where η∈[0,1). Then T has an FP.
Definition 2.9. [28] An element u0∈U is a CFP of the mappings S,T: U→CB(U) if u0∈Tu0∩Su0.
First we define that δ(u,A):=infν∈Aδ(u,ν). Now, we present our first main result.
Theorem 3.1. Let (U,δ) be a complete CM-space. Let S,T: U→CB(U) be a pair of multi-valued mappings satisfying
(b1δ(μ,ν)+b2[δ(μ,Sμ)+δ(ν,Tν)]+b3[δ(ν,Sμ)+δ(μ,Tν)])∈s(Sμ,Tν) | (3.1) |
for all μ,ν∈U, b1∈(0,1) and b2,b3≥0 with b1+2b2+2b3<1. Then S and T have a CFP in U.
Proof. Fix μ0∈U and let there exists μ1∈U such that μ1∈Sμ0. Then, from (3.1), we have
(b1δ(μ0,μ1)+b2[δ(μ0,Sμ0)+δ(μ1,Tμ1)]+b3[δ(μ1,Sμ0)+δ(μ0,Tμ1)])∈s(Sμ0,Tμ1). |
Since μ1∈Sμ0 and by Lemma 2.5(ⅲ), we have
(b1δ(μ0,μ1)+b2[δ(μ0,μ1)+δ(μ1,Tμ1)]+b3[δ(μ1,μ1)+δ(μ0,Tμ1)])∈s(μ1,Tμ1). |
Then there exists μ2∈Tμ1 such that
(b1δ(μ0,μ1)+b2[δ(μ0,Sμ0)+δ(μ1,μ2)]+b3[δ(μ1,Sμ0)+δ(μ0,μ2)])∈s(δ(μ1,μ2)). |
This implies that
δ(μ1,μ2)≤b1δ(μ0,μ1)+b2[δ(μ0,μ1)+δ(μ1,μ2)]+b3δ(μ0,μ2)≤b1δ(μ0,μ1)+b2[δ(μ0,μ1)+δ(μ1,μ2)]+b3[δ(μ0,μ1)+δ(μ1,μ2)]. |
After simplification, we obtain
δ(μ1,μ2)≤βδ(μ0,μ1),where β=b1+b2+b31−(b2+b3)<1. | (3.2) |
Again from (3.1), we have
(b1δ(μ2,μ1)+b2[δ(μ2,Sμ2)+δ(μ1,Tμ1)]+b3[δ(μ1,Sμ2)+δ(μ2,Tμ1)])∈s(Sμ2,Tμ1). |
Since μ2∈Tμ1, and by Lemma 2.5(ⅲ), we have
(b1δ(μ2,μ1)+b2[δ(μ2,Sμ2)+δ(μ1,μ2)]+b3[δ(μ1,Sμ2)+δ(μ2,μ2)])∈s(μ2,Sμ2). |
Then there exists μ3∈Sμ2 such that
(b1δ(μ2,μ1)+b2[δ(μ2,μ3)+δ(μ1,μ2)]+b3[δ(μ1,μ3)+δ(μ2,μ2)])∈s(δ(μ2,μ3)). |
This implies that
δ(μ2,μ3)≤b1δ(μ2,μ1)+b2[δ(μ2,μ3)+δ(μ1,μ2)]+b3δ(μ1,μ3)≤b1δ(μ2,μ1)+b2[δ(μ2,μ3)+δ(μ1,μ2)]+b3[δ(μ1,μ2)+δ(μ2,μ3)]. |
After simplification, we obtain
δ(μ2,μ3)≤βδ(μ1,μ2), | (3.3) |
where
β=b1+b2+b31−(b2+b3)<1. |
From (3.2) and (3.3), we have
δ(μ2,μ3)≤βδ(μ2,μ1)≤β2δ(μ0,μ1). |
By repeatedly applying the above arguments we construct a sequence {μn} in U such that
μ2n+1∈Sμ2n, and μ2n+2∈Tμ2n+1, ∀ n∈N. |
And
δ(μn,μn+1)≤βδ(μn−1,μn), | (3.4) |
where β is as in (3.3). Thus, by induction, we obtain
δ(μn,μn+1)≤βnδ(μ0,μ1). | (3.5) |
We claim that {μn} is a Cauchy sequence. Let m>n; then, by the triangular inequality and from (3.5), we have
δ(μn,μm)≤δ(μn,μn+1)+δ(μn+1,μn+2)+⋯+δ(μm−1,μm)≤βnδ(μ0,μ1)+βn+1δ(μ0,μ1)+⋯+βm−1δ(μ0,μ1)≤βn(1+β+β2+⋯+βm−n−1+⋯)δ(μ0,μ1)≤βn1−βδ(μ0,μ1)→θas n→+∞. |
By Lemma 2.4(ⅱ), {μn} is a Cauchy sequence in (U,δ). Since (U,δ) is complete, there exists ω1∈U such that μn→ω1 as n→+∞. Therefore,
limn→+∞μ2n+1=limn→+∞μ2n+2=ω1. | (3.6) |
Now, we have to prove that ω1∈Sω1. From (3.1), we have
(b1δ(ω1,μ2n+1)+b2[δ(ω1,Sω1)+δ(μ2n+1,Tμ2n+1)]+b3[δ(ω1,Tμ2n+1)+δ(μ2n+1,Sω1)])∈s(Tμ2n+1,Sω1). |
Since μ2n+2∈Tμ2n+1 and by Lemma 2.5(ⅲ), we have
(b1δ(ω1,μ2n+1)+b2[δ(ω1,Sω1)+δ(μ2n+1,μ2n+2)]+b3[δ(ω1,μ2n+2)+δ(μ2n+1,Sω1)])∈s(μ2n+2,Sω1). |
Then there exists vn∈Sw1 such that
(b1δ(ω1,μ2n+1)+b2[δ(ω1,vn)+δ(μ2n+1,μ2n+2)]+b3[δ(ω1,μ2n+2)+δ(μ2n+1,vn)])∈s(δ(μ2n+2,vn)). |
This implies that
δ(μ2n+2,vn)≤b1δ(ω1,μ2n+1)+b2[δ(ω1,vn)+δ(μ2n+1,μ2n+2)]+b3[δ(ω1,μ2n+2)+δ(μ2n+1,vn)]≤b1δ(ω1,μ2n+1)+b2[δ(ω1,μ2n+2)+δ(μ2n+2,vn)+δ(μ2n+1,ω1)+δ(ω1,μ2n+2)]+b3[δ(ω1,μ2n+2)+δ(μ2n+1,ω1)+δ(ω1,μ2n+2)+δ(μ2n+2,vn)]=2(b2+b3)δ(ω1,μ2n+2)+(b1+b2+b3)δ(ω1,μ2n+1)+(b2+b3)δ(μ2n+2,vn). |
After simplification, we get that
δ(μ2n+2,vn)≤2(b2+b3)1−b2−b3δ(ω1,μ2n+2)+b1+b2+b31−b2−b3δ(ω1,μ2n+1). |
Now, by taking the limit as n→+∞, we get that
limn→+∞δ(μ2n+2,vn)=θ. |
Therefore, since
δ(ω1,vn)≤δ(ω1,μ2n+2)+δ(μ2n+2,vn) |
by Lemma 2.4, we deduce that limn→+∞vn=ω1. Since Sω1 is closed, sequentially, we obtain ω1∈Sω1.
Similarly, we can prove that ω1∈Tω1. Hence, it is proved that the mappings S and T have a CFP in U, that is, ω1∈Sω1∩Tω1.
By putting the constants b3=0 and b2=0 in Theorem 3.1, we get the following two corollaries, respectively.
Corollary 3.2. Let (U,δ) be a complete CM-space. Let S,T: U→CB(U) be a pair of multi-valued mappings satisfying
b1δ(μ,ν)+b2[δ(μ,Sμ)+δ(ν,Tν)]∈s(Sμ,Tν) | (3.7) |
for all μ,ν∈U, b1∈(0,1) and b2≥0 with (b1+2b2)<1. Then S and T have a CFP in U.
Corollary 3.3. Let (U,δ) be a complete CM-space. Let S,T: U→CB(U) be a pair of multi-valued mappings satisfying
b1δ(μ,ν)+b3[δ(ν,Sμ)+δ(μ,Tν)]∈s(Sμ,Tν) | (3.8) |
for all μ,ν∈U, b1∈(0,1) and b3≥0 with (b1+2b3)<1. Then S and T have a CFP in U.
If we put S=T in Theorem 3.1, we get the following corollary:
Corollary 3.4. Let (U,δ) be a complete CM-space. Let S: U→CB(U) be a multi-valued mapping such that
(b1δ(μ,ν)+b2[δ(μ,Sμ)+δ(ν,Sν)]+b3[δ(ν,Sμ)+δ(μ,Sν)])∈s(Sμ,Sν) | (3.9) |
for all μ,ν∈U, b1∈(0,1) and b2,b3≥0 with (b1+2b2+2b3)<1. Then S has an FP in U.
Remark 3.5. In the context of complete M-spaces instead of complete CM-spaces, if we put b2=b3=0 and S=T in Theorem 3.1, then we obtain Nadler's result [26].
In the sense of Nadler's multi-valued concept [26], Theorem 3.1 can be stated as follows:
Corollary 3.6. Let (U,δ) be a complete CM-space. Let S,T: U→CB(U) be a pair of multi-valued mappings such that:
Hδ(Sμ,Tν)≤b1δ(μ,ν)+b2[δ(μ,Sμ)+δ(ν,Tν)]+b3[δ(ν,Sμ)+δ(μ,Tν)] | (3.10) |
for all μ,ν∈U, b1∈(0,1), and b2,b3≥0 with (b1+2b2+2b3)<1. Then S and T have a CFP in U.
Now, we present our second main result.
Theorem 3.7. Let (U,δ) be a complete CM-space. Let S,T: U→CB(U) be a pair of multi-valued mappings verifying
(b1δ(μ,ν)+b2max{δ(μ,Sμ),δ(ν,Tν),δ(ν,Sμ),δ(μ,Tν)})∈s(Sμ,Tν) | (3.11) |
for all μ,ν∈U, b1∈[0,1) and b2≥0 with (b1+2b2)<1. Then S and T have a CFP in U.
Proof. Fix μ0∈U and μ1∈Sμ0. Then, from (3.11), we have
(b1δ(μ0,μ1)+b2max{δ(μ0,Sμ0),δ(gμ1,Tμ1),δ(μ1,Sμ0),δ(μ0,Tμ1)})∈s(Sμ0,Tμ1). |
Thus by Lemma 2.5(ⅲ), we have
(b1δ(μ0,μ1)+b2max{δ(μ0,μ1),δ(gμ1,Tμ1),δ(μ1,μ1),δ(μ0,Tμ1)})∈s(μ1,Tμ1). |
Then there exists μ2∈Tμ1 such that
(b1δ(μ0,μ1)+b2max{δ(μ0,μ1),δ(μ1,μ2),δ(μ0,μ2)})∈s(δ(μ1,μ2)). |
This implies that
δ(μ1,μ2)≤b1δ(μ0,μ1)+b2max{δ(μ0,μ1),δ(μ1,μ2),δ(μ0,μ2)}. | (3.12) |
We may have the following three cases:
(a) If δ(μ0,μ1) is the maximum term of {δ(μ0,μ1),δ(μ1,μ2),δ(μ0,μ2)}, then, from (3.12), we get that
δ(μ1,μ2)≤(b1+b2)δ(μ0,μ1). | (3.13) |
(b) If δ(μ1,μ2) is the maximum term of {δ(μ0,μ1),δ(μ1,μ2),δ(μ0,μ2)}, then, from (3.12), we get that
δ(μ1,μ2)≤b11−b2δ(μ0,μ1). | (3.14) |
(c) If δ(μ0,μ2) is the maximum term of {δ(μ0,μ1),δ(μ1,μ2),δ(μ0,μ2)}, then, from (3.12) and the triangle inequality, we get that
δ(μ1,μ2)≤b1+b21−b2δ(μ0,μ1). | (3.15) |
Let us define
β:=max{(b1+b2),(b11−b2),(b1+b21−b2)}<1, |
where (b1+2b2)<1; then, from (3.13)–(3.15), we have that
δ(μ1,μ2)≤βδ(μ0,μ1). | (3.16) |
Again from (3.11), we have
(b1δ(μ2,μ1)+b2max{δ(μ2,Sμ2),δ(μ1,Tμ1),δ(μ1,Sμ2),δ(μ2,Tμ1)})∈s(Sμ2,Tμ1). |
Since μ2∈Tμ1, and by Lemma 2.5(ⅲ), we have
(b1δ(μ1,μ2)+b2max{δ(μ2,Sμ2),δ(μ1,μ2),δ(μ1,Sμ2),δ(μ2,μ2)})∈s(μ2,Sμ2). |
Then there exists μ3∈Sμ2 such that
(b1δ(μ1,μ2)+b2max{δ(μ2,μ3),δ(μ1,μ2),δ(μ1,μ3)})∈s(δ(μ3,μ2)). |
This implies that
δ(μ2,μ3)≤b1δ(μ1,μ2)+b2max{δ(μ1,μ2),δ(μ2,μ3),δ(μ1,μ3)}. | (3.17) |
Then, we may have the following three cases:
(a) If δ(μ1,μ2) is the maximum term of {δ(μ1,μ2),δ(μ2,μ3),δ(μ1,μ3)}, then, from (3.17), we get that
δ(μ2,μ3)≤(b1+b2)δ(μ1,μ2). | (3.18) |
(b) If δ(μ2,μ3) is the maximum term of {δ(μ1,μ2),δ(μ2,μ3),δ(μ1,μ3)}, then, from (3.17), we have
δ(μ2,μ3)≤b11−b2δ(μ1,μ2). | (3.19) |
(c) If δ(μ1,μ3) is the maximum term of {δ(μ1,μ2),δ(μ2,μ3),δ(μ1,μ3)}, then, from (3.17) and the triangle inequality, we get that
δ(μ2,μ3)≤b1+b21−b2δ(μ1,μ2). | (3.20) |
Then from (3.18)–(3.20), we find that
δ(μ2,μ3)≤βδ(μ1,μ2), | (3.21) |
where β is as in (3.16). From (3.16) and (3.21), we have
δ(μ2,μ3)≤βδ(μ2,μ1)≤β2δ(μ0,μ1). |
By repeatedly applying the above arguments we construct a sequence {μn} in U such that
μ2n+1∈Sμ2n, and μ2n+2∈Tμ2n+1, ∀ n∈N. |
And
δ(μn,μn+1)≤βδ(μn−1,μn), | (3.22) |
where β is as in (3.16).
Thus, by induction, we obtain
δ(μn,μn+1)≤βnδ(μ0,μ1), ∀ n∈N. | (3.23) |
Now, we have to show that {μn} is a Cauchy sequence. Let m>n; then, by the triangular inequality and from (3.22), we have
δ(μn,μm)≤δ(μn,μn+1)+δ(μn+1,μn+2)+⋯+δ(μm−1,μm)≤βnδ(μ0,μ1)+βn+1δ(μ0,μ1)+⋯+βm−1δ(μ0,μ1)≤βn(1+β+β2+⋯+βm−n−1+⋯)δ(μ0,μ1)≤βn1−βδ(μ0,μ1)→θas n→+∞. |
By Lemma 2.4(ⅱ), {μn} is a Cauchy sequence in (U,δ). Since (U,δ) is complete, there exists ω1∈U such that μn→ω1 as n→+∞. Therefore,
limn→+∞μ2n+1=limn→+∞μ2n+2=ω1. | (3.24) |
Now, we have to prove that ω1∈Sω1. From (3.11), we have
(b1δ(ω1,μ2n+1)+b2max{δ(ω1,Sω1),δ(μ2n+1,Tμ2n+1),δ(ω1,Tμ2n+1),δ(μ2n+1,Sω1)})∈s(Sω1,Tμ2n+1). |
Since μ2n+2∈Tμ2n+1 and by Lemma 2.5(ⅲ), we have
(b1δ(ω1,μ2n+1)+b2max{δ(ω1,Sω1),δ(μ2n+1,μ2n+2),δ(ω1,μ2n+2),δ(μ2n+1,Sω1)})∈s(μ2n+2,Sω1). |
Then, there exists vn∈Sω1 such that
(b1δ(ω1,μ2n+1)+b2max{δ(ω1,vn),δ(μ2n+1,μ2n+2),δ(ω1,μ2n+2),δ(μ2n+1,vn)})∈s(δ(μ2n+2,vn)). |
This implies that
δ(μ2n+2,vn)≤b1δ(ω1,μ2n+1)+b2max{δ(ω1,vn),δ(μ2n+1,μ2n+2),δ(ω1,μ2n+2),δ(μ2n+1,vn)}. | (3.25) |
Then, we may have the following four cases:
(a) If δ(ω1,vn) is the maximum term of {δ(ω1,vn),δ(μ2n+1,μ2n+2),δ(ω1,μ2n+2),δ(μ2n+1,vn)}, then, from (3.25) and the triangle inequality, we get that
δ(μ2n+2,vn)≤b11−b2δ(ω1,μ2n+1)+b21−b2δ(ω1,μ2n+2). | (3.26) |
(b) If δ(μ2n+1,μ2n+2) is the maximum term of {δ(ω1,vn),δ(μ2n+1,μ2n+2),δ(ω1,μ2n+2),δ(μ2n+1,vn)}, then, from (3.25) and the triangle inequality, we get that
δ(μ2n+2,vn)≤(b1+b2)δ(ω1,μ2n+1)+b2δ(ω1,μ2n+2). | (3.27) |
(c) If δ(ω1,μ2n+2) is the maximum term of {δ(ω1,vn),δ(μ2n+1,μ2n+2),δ(ω1,μ2n+2),δ(μ2n+1,vn)}, then, from (3.25), we get that
δ(μ2n+2,vn)≤b1δ(ω1,μ2n+1)+b2δ(ω1,μ2n+2). | (3.28) |
(d) If δ(μ2n+1,vn) is the maximum term of {δ(ω1,vn),δ(μ2n+1,μ2n+2),δ(ω1,μ2n+2),δ(μ2n+1,vn)}, then, from (3.25) and the triangle inequality, we get that
δ(μ2n+2,vn)≤b1+b21−b2δ(ω1,μ2n+1)+b21−b2δ(ω1,μ2n+2). | (3.29) |
Then, we define
λ1:=max{b11−b2,(b1+b2),b1,b1+b21−b2} |
and
λ2:=max{b21−b2,b2}. |
Then, from (3.26)–(3.29), we have that
δ(μ2n+2,vn)≤λ1δ(ω1,μ2n+1)+λ2δ(ω1,μ2n+2). |
Now, by taking the limit as n→+∞, we get that
limn→+∞δ(μ2n+2,vn)=θ. |
As in the proof of Theorem (3.1), this implies that
limn→+∞vn=ω1. |
Since Sω1 is closed, sequentially we deduce that ω1∈Sω1. Similarly, we can prove that ω1∈Tω1. Hence, it is proved that the mappings S and T have a CFP in U, that is, ω1∈Sω1∩Tω1.
By reducing the maximum term in Theorem 3.7, we get the following corollaries:
Corollary 3.8. Let (U,δ) be a complete CM-space. Let S,T: U→CB(U) be a pair of multi-valued mappings satisfying
b1δ(μ,ν)+b2max{δ(μ,Sμ),δ(ν,Tν)}∈s(Sμ,Tν) | (3.30) |
for all μ,ν∈U, b1∈(0,1) and b2≥0 with (b1+b2)<1. Then S and T have a CFP in U.
Corollary 3.9. Let (U,δ) be a complete CM-space. Let S,T: U→CB(U) be a pair of multi-valued mappings satisfying
b1δ(μ,ν)+b2max{δ(ν,Sμ),δ(μ,Tν)}∈s(Sμ,Tν) | (3.31) |
for all μ,ν∈U, b1∈(0,1) and b2≥0 with (b1+2b2)<1. Then S and T have a CFP in U.
If we put S=T in Theorem 3.7, we get the following corollary:
Corollary 3.10. Let (U,δ) be a complete CM-space. Let S: U→CB(U) be a multi-valued mapping such that
(b1δ(μ,ν)+b2max{δ(μ,Sμ),δ(ν,Sν),δ(ν,Sμ),δ(μ,Sν)})∈s(Sμ,Sν) | (3.32) |
for all μ,ν∈U, b1∈(0,1) and b2≥0 with (b1+2b2)<1. Then S has an FP in U.
In the sense of Nadler's multi-valued concept [26], Theorem 3.7 can be stated as follows:
Corollary 3.11. Let (U,δ) be a complete CM-space. Let S,T: U→CB(U) be a pair of multi-valued mappings so that
Hδ(Sμ,Tν)≤b1δ(μ,ν)+b2max{δ(μ,Sμ),δ(ν,Tν),δ(ν,Sμ),δ(μ,Tν)} | (3.33) |
for all μ,ν∈U, b1∈(0,1) and b2≥0 with (b1+2b2)<1. Then S and T have a CFP in U.
Example 3.12. Let U=[0,1] and the cone
P:={u∈E:u(t)≥0, for t∈[0,1]} |
on E where
E=C([0,1],R) |
denoting continuous functions on [0, 1]. Then P is a normal cone with respect to the norm of the space E with the constant K=1. A cone metric δ: U×U→E is defined as
δ(u1,u2)=|u1−u2| |
for all u1,u2∈U. Let B be a family of nonempty closed and bounded subsets of U of the form
B={[0,u]:u∈U}. |
Now, we define a pair of multi-valued mappings S,T:U→B by
Su=Tu=[0,2u7]. |
Moreover, for u1,u2∈U(u1≠u2) and u1,u2≠0, let
b1=27 and b2=b3=221. |
Then, we have that
(27δ(μ,ν)+221[δ(μ,Sμ)+δ(ν,Tν)]+221[δ(ν,Sμ)+δ(μ,Tν)])∈s(Sμ,Tν)⇔62147(μ+ν)∈s(Sμ,Tν)⇔62147(μ+ν)∈(⋂x∈Sμ⋃y∈Tνs(δ(x,y)))∩(⋂y∈Tν⋃x∈Sμs(δ(x,y)))⇔(∃x∈Sμ)(∃y∈Tν)62147(μ+ν)∈s(δ(x,y))⇔s(δ(x,y))≤62147(μ+ν)=(b1δ(μ,ν)+b2[δ(μ,Sμ)+δ(ν,Tν)]+b3[δ(ν,Sμ)+δ(μ,Tν)]). |
Now, by taking
x=27μ, y=27ν |
and
(b1+2b2+2b3)=23<1, |
all hypothesis of Theorem 3.1 are satisfied, and the pair of multi-valued mappings S and T have a CFP in U, that is, "0".
In this section, we present a supportive application of integral equations for this new theory. A number of researchers have used various applications in differential and integral equations in the context of M-spaces for FP results. Some of their works can be found in [4,41,42,43] and the references therein. Here in this section, we develop an approach for solving the nonlinear integral type problems represented by the following integral equations:
μ(ξ)=∫a0K1(ξ,s,μ(s))ds, and ν(ξ)=∫a0K2(ξ,s,ν(s))ds, | (4.1) |
where K1,K2: [0,a]×[0,a]×R→R are continuous with a>0. Let U=C([0,a],R) be the Banach space of all continuous functions defined on [0,a] and endowed with the usual supremum norm:
‖μ‖∞=maxξ∈[0,a]|μ(ξ)|, where μ∈C([0,a],R), |
and the induced metric (U,δ) is defined by
δ(μ,ν)=‖μ−ν‖∞ |
for all μ,ν∈U. Now, we are in the position to present the integral type application to support our work.
Theorem 4.1. Suppose that the following hypotheses are satisfied:
(1) Let K1,K2: [0,a]×[0,a]×R→R be continuous; for μ,ν∈U let Bμ,Bν∈U be defined as
Bμ(ξ)=∫a0K1(ξ,s,μ(s))dsandBν(ξ)=∫a0K2(ξ,s,ν(s))ds. | (4.2) |
Suppose that there exists a mapping
Γ:[0,a]×[0,a]→[0,+∞) with Γ(ξ,⋅)∈L1([0,a]) |
for all ξ∈[0,a] such that
|K1(ξ,s,μ(s))−K2(ξ,s,ν(s))|≤Γ(ξ,s)N∗(μ,ν),∀μ,ν∈U, and ξ,s∈[0,a], |
where
N∗(μ(s),ν(s))=N∗(μ,ν)=min{‖μ−ν‖∞,max{‖Bμ−μ‖∞,‖Bν−ν‖∞,‖Bμ−ν‖∞,‖Bν−μ‖∞}}. | (4.3) |
(2) Suppose also that
|Kμ(ξ,s,μ(s))|≤Γ(ξ,s)|μ(s)|, and |Kν(ξ,s,ν(s))|≤Γ(ξ,s)|ν(s)|, ∀μ,ν∈U. |
(3) Suppose further that there exists β∈(0,1) such that
βN∗(μ,ν)∈s(A,B)for μ∈A, ν∈B,and A,B⊆CB(U) | (4.4) |
where supξ∈[0,a]∫ξ0Γ(ξ,s)ds=β<1.
(4) Finally, suppose that there exists μ0∈U such that
μ0≤∫a0K1(ξ,s,μ0(s))ds, ∀ ξ∈[0,a]. |
Then the integral equations in (4.1) have a common solution in U.
Proof. Define the integral operators S,T: U→CB(U) by
Bμ(ξ)∈Sμ(ξ)=A and Bν(ξ)∈Tν(ξ)=B, | (4.5) |
for μ(ξ)∈A, ν(ξ)∈B and A,B⊆CB(U). Notice that S and T are well defined and the equations of (4.1) have a common solution if and only if S and T have a common solution, that is the CFP of the mappings S and T in U. Precisely, we have to prove that Theorem 3.7 is applicable to the operators defined in (4.5). Then, we may have the following two main cases:
(1) If ‖μ−ν‖∞ is the minimum term in (4.3), then N∗(μ,ν)=‖μ−ν‖∞. Now, from (4.4) and (4.5), we have
β‖μ−ν‖∞=βδ(μ,ν)∈s(A,B)=s(Sμ,Tν) for μ∈A, ν∈B and A,B⊆CB(U). | (4.6) |
The integral operators defined in (4.5) satisfy all of the hypotheses of Theorem 3.7 with β=b1 and b2=0 in (3.11). Thus, the integral equations in (4.1) have a common solution in U.
(2) If max{‖Bμ−μ‖∞,‖Bν−ν‖∞,‖Bμ−ν‖∞,‖Bν−μ‖∞} is the minimum term in (4.3), then
N∗(μ,ν)=max{‖Bμ−μ‖∞,‖Bν−ν‖∞,‖Bμ−ν‖∞,‖Bν−μ‖∞}. | (4.7) |
Then again we may have the following four subcases:
(ⅰ) If ‖Bμ−μ‖∞ is the maximum term in (4.7), then N∗(μ,ν)=‖Bμ−μ‖∞. Now, from (4.4) and (4.5), we have
β‖Bμ−μ‖∞∈s(δ(μ,A))∈s(A,B)=s(Sμ,Tν) for μ∈A, ν∈B and A,B⊆CB(U). | (4.8) |
(ⅱ) If ‖Bν−ν‖∞ is the maximum term in (4.7), then N∗(μ,ν)=‖Bν−ν‖∞. Now, from (4.4) and (4.5), we have
β‖Bν−ν‖∞∈s(δ(ν,B))∈s(A,B)=s(Sμ,Tν) for μ∈A, ν∈B and A,B⊆CB(U). | (4.9) |
(ⅲ) If ‖Bμ−ν‖∞ is the maximum term in (4.7), then N∗(μ,ν)=‖Bμ−ν‖∞. Now, from (4.4) and (4.5), we have
β‖Bμ−ν‖∞∈s(δ(ν,A))∈s(A,B)=s(Sμ,Tν) for μ∈A, ν∈B and A,B⊆CB(U). | (4.10) |
(ⅳ) If ‖Bν−μ‖∞ is the maximum term in (4.7), then N∗(μ,ν)=‖Bν−μ‖∞. Now, from (4.4) and (4.5), we have
β‖Bν−μ‖∞∈s(δ(μ,A))∈s(A,B)=s(Sμ,Tν) for μ∈A, ν∈B and A,B⊆CB(U). | (4.11) |
Hence, from (4.8)–(4.11), the integral operators S and T, satisfy all of the hypotheses of Theorem 3.7 with β=b2 and b1=0 in (3.11). Thus, the integral equations in (4.1) have a common solution in U.
In this paper, we have proved some new types of multi-valued contraction results for a pair of multi-valued mappings on CM-spaces. In support of our work, we presented an illustrative example. Our main results improved and modified many results published in the last few decades. In addition, we established a supportive application of nonlinear integral equations to unify our work. This new theory will play a very good role in the theory of FPs. This new concept has a potency to modify in different directions and prove different types of multi-valued contraction results for FPs, CFPs and coincidence points in the context of different types of M-spaces with different types of nonlinear integral equations and differential equations. Furthermore, we shall present a problem, i.e., whether the said theory in this paper is applicable or not to the theory of fractional derivatives (especially in the sense of Abu-Shady and Kaabar [44,45]).
This work was supported by the Basque Government under Grant IT1555-22.
The authors declare that they have no conflicts of interest.
[1] |
J. Buckley, I. James, Linear regression with censored data, Biometrika, 66 (1979), 429–436. https://doi.org/10.1093/biomet/66.3.429 doi: 10.1093/biomet/66.3.429
![]() |
[2] |
D. R. Cox, Regression models and life-tables (with discussion), J. Roy. Stat. Soc. Ser. B, 34 (1972), 187–220. https://doi.org/10.1111/j.2517-6161.1972.tb00899.x doi: 10.1111/j.2517-6161.1972.tb00899.x
![]() |
[3] |
H. Chai, Q. Z. Zhang, J. Huang, S. G. Ma, Inference for low-dimensional covariates in a high-dimensional accelerated failure time model, Stat. Sinica, 29 (2019), 877–894. https://doi.org/10.5705/ss.202016.0449 doi: 10.5705/ss.202016.0449
![]() |
[4] |
T. Choi, S. Choi, A fast algorithm for the accelerated failure time model with high-dimensional time-to-event data, J. Stat. Comput. Simul., 91 (2021), 3385–3403. https://doi.org/10.1080/00949655.2021.1927034 doi: 10.1080/00949655.2021.1927034
![]() |
[5] |
L. Dicker, B. S. Huang, X. H. Lin, Variable selection and estimation with the seamless-L 0 penalty, Stat. Sinica, 23 (2013), 929–962. https://dx.org/10.5705/ss.2011.074 doi: 10.5705/ss.2011.074
![]() |
[6] |
J. Q. Fan, R. Z. Li, Variable selection via nonconcave penalized likelihood and its oracle properties, J. Am. Stat. Assoc., 96 (2001), 1348–1360. https://doi.org/10.1198/016214501753382273 doi: 10.1198/016214501753382273
![]() |
[7] |
J. Huang, S. G. Ma, H. L. Xie, Regularized estimation in the accelerated failure time model with high-dimensional covariates, Biometrics, 62 (2006), 813–820. https://doi.org/10.1111/j.1541-0420.2006.00562.x doi: 10.1111/j.1541-0420.2006.00562.x
![]() |
[8] |
J. Huang, S. G. Ma, Variable selection in the accelerated failure time model via the bridge method, Lifetime Data Anal., 16 (2010), 176–195. https://doi.org/10.1007/s10985-009-9144-2 doi: 10.1007/s10985-009-9144-2
![]() |
[9] | S. M. Hu, J. S. Rao, Sparse penalization with censoring constraints for estimating high dimensional AFT models with applications to microarray data analysis, Technical reports, University of Miami, 2010. |
[10] | J. D. Kalbfleisch, R. L. Prentice, The statistical analysis of failure time data, John Wiley & Sons. Inc., New Jersey, 2 (2011), 168–170. https://doi.org/10.1016/0197-2456(81)90009-X |
[11] |
Y. D. Kim, H. Choi, H. S. Oh, Smoothly clipped absolute deviation on high dimensions, J. Am. Stat. Assoc., 103 (2008), 1665–1673. https://doi.org/10.1198/016214508000001066 doi: 10.1198/016214508000001066
![]() |
[12] |
Y. Li, M. X. Liang, L. Mao, S. J. Wang, Robust estimation and variable selection for the accelerated failure time model, Stat. Med., 40 (2021), 4473–4491. https://doi.org/10.1002/sim.9042 doi: 10.1002/sim.9042
![]() |
[13] |
Y. Ritov, Estimation in a linear regression model with censored data, Ann. Stat., 18 (1990), 354–372. https://doi.org/10.1214/aos/1176347502 doi: 10.1214/aos/1176347502
![]() |
[14] |
W. Stute, Consistent estimation under random censorship when covariables are present, J. Multivariate Anal., 45 (1993), 89–103. https://doi.org/10.1006/jmva.1993.1028 doi: 10.1006/jmva.1993.1028
![]() |
[15] |
W. Stute, Distributional convergence under random censorship when covariables are present, Scand. J. Stat., 23 (1996), 461–471. https://doi.org/10.1016/s0167-7152(98)00069-8 doi: 10.1016/s0167-7152(98)00069-8
![]() |
[16] |
R. Tibshirani, Regression shrinkage and selection via the lasso, J. Roy. Stat. Soc. B, 58 (1996), 267–288. https://doi.org/10.1111/j.2517-6161.1996.tb02080.x doi: 10.1111/j.2517-6161.1996.tb02080.x
![]() |
[17] | A. A. Tsiatis, Estimating regression parameters using linear rank tests for censored data, Ann. Stat., 18 (1990), 354–372. https://doi.org/354-372.10.1214/aos/1176347504 |
[18] |
X. G. Wang, L. X. Song, Adaptive Lasso variable selection for the accelerated failure models, Commun. Stat.-Theor. M., 40 (2011), 4372–4386. https://doi.org/10.1080/03610926.2010.513785 doi: 10.1080/03610926.2010.513785
![]() |
[19] |
H. Zou, The adaptive lasso and its oracle properties, J. Am. Stat. Assoc., 101 (2006), 1418–1429. https://doi.org/10.1198/016214506000000735 doi: 10.1198/016214506000000735
![]() |
[20] | H. Zou, Nearly unbiased variable selection under minimax concave penalty, J. Am. Stat. Assoc., 38 (2010), 894–942. https://doi.org/894-942.10.1214/09-AOS729 |
[21] | W. J. Fu, Penalized regressions: The bridge versus the lasso, J. Comput. Graph. Stat., 7 (1998). https://doi.org/397-416.10.1214/09-AOS729 |
[22] |
M. H. R. Khan, J. E. H. Shaw, Variable selection for survival data with a class of adaptive elastic net techniques, Stat. Comput., 26 (2016), 725–741. https://doi.org/10.1007/s11222-015-9555-8 doi: 10.1007/s11222-015-9555-8
![]() |