Loading [MathJax]/jax/output/SVG/jax.js
Research article

Novel efficient estimators of finite population mean in stratified random sampling with application

  • Unbiased estimators are valuable when no auxiliary information is available beyond the primary study variables. However, once auxiliary information is accessible, biased estimators with smaller Mean Square Error (MSE) often outperform unbiased estimators that have large variances. We sought to develop new estimators that incorporate a single auxiliary variable in stratified random sampling. This study contributes to the field by introducing two distinct families of estimators designed to estimate the finite population mean. We conducted a theoretical evaluation of the estimators' performance by examining bias and MSE derived under first-order approximation. Additionally, we established the theoretical conditions necessary for the proposed estimator families to exhibit superior performance compared with existing alternatives. Empirical and simulation-based studies demonstrated significant improvements in estimators over competing estimators for finite-population parameter estimation.

    Citation: Khazan Sher, Muhammad Ameeq, Muhammad Muneeb Hassan, Basem A. Alkhaleel, Sidra Naz, Olyan Albalawi. Novel efficient estimators of finite population mean in stratified random sampling with application[J]. AIMS Mathematics, 2025, 10(3): 5495-5531. doi: 10.3934/math.2025254

    Related Papers:

    [1] Meshari Alesemi . Innovative approaches of a time-fractional system of Boussinesq equations within a Mohand transform. AIMS Mathematics, 2024, 9(10): 29269-29295. doi: 10.3934/math.20241419
    [2] Azzh Saad Alshehry, Humaira Yasmin, Ali M. Mahnashi . Analyzing fractional PDE system with the Caputo operator and Mohand transform techniques. AIMS Mathematics, 2024, 9(11): 32157-32181. doi: 10.3934/math.20241544
    [3] Aisha Abdullah Alderremy, Rasool Shah, Nehad Ali Shah, Shaban Aly, Kamsing Nonlaopon . Comparison of two modified analytical approaches for the systems of time fractional partial differential equations. AIMS Mathematics, 2023, 8(3): 7142-7162. doi: 10.3934/math.2023360
    [4] Musawa Yahya Almusawa, Hassan Almusawa . Numerical analysis of the fractional nonlinear waves of fifth-order KdV and Kawahara equations under Caputo operator. AIMS Mathematics, 2024, 9(11): 31898-31925. doi: 10.3934/math.20241533
    [5] M. Mossa Al-Sawalha, Khalil Hadi Hakami, Mohammad Alqudah, Qasem M. Tawhari, Hussain Gissy . Novel Laplace-integrated least square methods for solving the fractional nonlinear damped Burgers' equation. AIMS Mathematics, 2025, 10(3): 7099-7126. doi: 10.3934/math.2025324
    [6] Aslı Alkan, Halil Anaç . The novel numerical solutions for time-fractional Fornberg-Whitham equation by using fractional natural transform decomposition method. AIMS Mathematics, 2024, 9(9): 25333-25359. doi: 10.3934/math.20241237
    [7] 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
    [8] Emad Salah, Ahmad Qazza, Rania Saadeh, Ahmad El-Ajou . A hybrid analytical technique for solving multi-dimensional time-fractional Navier-Stokes system. AIMS Mathematics, 2023, 8(1): 1713-1736. doi: 10.3934/math.2023088
    [9] Qasem M. Tawhari . Advanced analytical techniques for fractional Schrödinger and Korteweg-de Vries equations. AIMS Mathematics, 2025, 10(5): 11708-11731. doi: 10.3934/math.2025530
    [10] Ritu Agarwal, Mahaveer Prasad Yadav, Dumitru Baleanu, S. D. Purohit . Existence and uniqueness of miscible flow equation through porous media with a non singular fractional derivative. AIMS Mathematics, 2020, 5(2): 1062-1073. doi: 10.3934/math.2020074
  • Unbiased estimators are valuable when no auxiliary information is available beyond the primary study variables. However, once auxiliary information is accessible, biased estimators with smaller Mean Square Error (MSE) often outperform unbiased estimators that have large variances. We sought to develop new estimators that incorporate a single auxiliary variable in stratified random sampling. This study contributes to the field by introducing two distinct families of estimators designed to estimate the finite population mean. We conducted a theoretical evaluation of the estimators' performance by examining bias and MSE derived under first-order approximation. Additionally, we established the theoretical conditions necessary for the proposed estimator families to exhibit superior performance compared with existing alternatives. Empirical and simulation-based studies demonstrated significant improvements in estimators over competing estimators for finite-population parameter estimation.



    The purpose of this paper is to study the global behavior of the following max-type system of difference equations of the second order with four variables and period-two parameters

    {xn=max{An,zn1yn2},yn=max{Bn,wn1xn2},zn=max{Cn,xn1wn2},wn=max{Dn,yn1zn2},  nN0{0,1,2,}, (1.1)

    where An,Bn,Cn,DnR+(0,+) are periodic sequences with period 2 and the initial values xi,yi,zi,wiR+ (1i2). To do this we will use some methods and ideas which stems from [1,2]. For a more complex variant of the method, see [3]. A solution {(xn,yn,zn,wn)}+n=2 of (1.1) is called an eventually periodic solution with period T if there exists mN such that (xn,yn,zn,wn)=(xn+T,yn+T,zn+T,wn+T) holds for all nm.

    When xn=yn and zn=wn and A0=A1=B0=B1=α and C0=C1=D0=D1=β, (1.1) reduces to following max-type system of difference equations

    {xn=max{α,zn1xn2},zn=max{β,xn1zn2},  nN0. (1.2)

    Fotiades and Papaschinopoulos in [4] investigated the global behavior of (1.2) and showed that every positive solution of (1.2) is eventually periodic.

    When xn=zn and yn=wn and An=Cn and Bn=Dn, (1.1) reduces to following max-type system of difference equations

    {xn=max{An,yn1xn2},yn=max{Bn,xn1yn2},  nN0. (1.3)

    Su et al. in [5] investigated the periodicity of (1.3) and showed that every solution of (1.3) is eventually periodic.

    In 2020, Su et al. [6] studied the global behavior of positive solutions of the following max-type system of difference equations

    {xn=max{A,yntxns},yn=max{B,xntyns},  nN0,

    where A,BR+.

    In 2015, Yazlik et al. [7] studied the periodicity of positive solutions of the max-type system of difference equations

    {xn=max{1xn1,min{1,pyn1}},yn=max{1yn1,min{1,pxn1}}, nN0, (1.4)

    where pR+ and obtained in an elegant way the general solution of (1.4).

    In 2016, Sun and Xi [8], inspired by the research in [5], studied the following more general system

    {xn=max{1xnm,min{1,pynr}},yn=max{1ynm,min{1,qxnt}},  nN0, (1.5)

    where p,qR+, m,r,tN{1,2,} and the initial conditions xi,yiR+ (1is) with s=max{m,r,t} and showed that every positive solution of (1.5) is eventually periodic with period 2m.

    In [9], Stević studied the boundedness character and global attractivity of the following symmetric max-type system of difference equations

    {xn=max{B,ypn1xpn2},yn=max{B,xpn1ypn2},  nN0,

    where B,pR+ and the initial conditions xi,yiR+ (1i2).

    In 2014, motivated by results in [9], Stević [10] further study the behavior of the following max-type system of difference equations

    {xn=max{B,ypn1zpn2},yn=max{B,zpn1xpn2},zn=max{B,xpn1ypn2}.  nN0, (1.6)

    where B,pR+ and the initial conditions xi,yi,ziR+ (1i2), and showed that system (1.6) is permanent when p(0,4).

    For more many results for global behavior, eventual periodicity and the boundedness character of positive solutions of max-type difference equations and systems, please readers refer to [11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30] and the related references therein.

    In this section, we study the global behavior of system (1.1). For any n1, write

    {x2n=A2nXn,y2n=B2nYn,z2n=C2nZn,w2n=D2nWn,x2n+1=A2n+1Xn,y2n+1=B2n+1Yn,z2n+1=C2n+1Zn,w2n+1=D2n+1Wn.

    Then, (1.1) reduces to the following system

    {Xn=max{1,C2n1Zn1A2nB2nYn1},Yn=max{1,D2n1Wn1B2nA2nXn1},Zn=max{1,A2nXnC2n+1D2n+1Wn1},Wn=max{1,B2nYnD2n+1C2n+1Zn1},Zn=max{1,A2n1Xn1C2nD2nWn1},Wn=max{1,B2n1Yn1D2nC2nZn1},Xn=max{1,C2nZnA2n+1B2n+1Yn1},Yn=max{1,D2nWnB2n+1A2n+1Xn1},  nN0. (2.1)

    From (2.1) we see that it suffices to consider the global behavior of positive solutions of the following system

    {un=max{1,bvn1aAUn1},Un=max{1,BVn1aAun1},vn=max{1,aunbBVn1},Vn=max{1,AUnbBvn1},  nN0, (2.2)

    where a,b,A,BR+, the initial conditions u1,U1,v1,V1R+. If (un,Un,vn,Vn,a,A,b,B)=(Xn,Yn,Zn,Wn,A2n,B2n,C2n1,D2n1), then (2.2) is the first four equations of (2.1). If (un,Un,vn,Vn,a,A,b,B)=(Zn,Wn,Xn,Yn,C2n,D2n,A2n1,B2n1), then (2.2) is the next four equations of (2.1). In the following without loss of generality we assume aA and bB. Let {(un,Un,vn,Vn)}n=1 be a positive solution of (2.2).

    Proposition 2.1. If ab<1, then there exists a solution {(un,Un,vn,Vn)}n=1 of (2.2) such that un=vn=1 for any n1 and limnUn=limnVn=.

    Proof. Let u1=v1=1 and U1=V1=max{baA,aAB,abB}+1. Then, from (2.2) we have

    {u0=max{1,bv1aAU1}=1,U0=max{1,BV1aAu1}=BV1aA,v0=max{1,au0bBV1}=1,V0=max{1,AU0bBv1}=V1ab,

    and

    {u1=max{1,bv0aAU0}=max{1,bBV1}=1,U1=max{1,BV0aAu0}=max{1,BV1aAab}=BV1aAab,v1=max{1,au1bBV0}=max{1,aabbBV1}=1,V1=max{1,AU1bBv0}=max{1,V1(ab)2}=V1(ab)2.

    Suppose that for some kN, we have

    {uk=1,Uk=BV1aA(ab)k,vk=1,Vk=V1(ab)k+1.

    Then,

    {uk+1=max{1,bvkaAUk}=max{1,b(ab)kBV1}=1,Uk+1=max{1,BVkaAuk}=max{1,BV1aA(ab)k+1}=BV1aA(ab)k+1,vk+1=max{1,auk+1bBVk}=max{1,a(ab)k+1bBV1}=1,Vk+1=max{1,AUk+1bBvk}=max{1,V1(ab)k+2}=V1(ab)k+2.

    By mathematical induction, we can obtain the conclusion of Proposition 2.1. The proof is complete.

    Now, we assume that ab1. Then, from (2.2) it follows that

    {un=max{1,bvn1aAUn1},Un=max{1,BVn1aAun1},vn=max{1,abBVn1,vn1ABUn1Vn1},Vn=max{1,AbBvn1,Vn1abun1vn1},  nN0. (2.3)

    Lemma 2.1. The following statements hold:

    (1) For any nN0,

    un, Un, vn, Vn[1,+). (2.4)

    (2) If ab1, then for any kN and nk+2,

    {un=max{1,baAUn1,bvkaA(AB)nk1Un1Un2Vn2UkVk},Un=max{1,BaAun1,BVkaA(ab)nk1un1un2vn2ukvk},vn=max{1,abBVn1,vk(AB)nkUn1Vn1UkVk},Vn=max{1,AbBvn1,Vk(ab)nkun1vn1ukvk}. (2.5)

    (3) If ab1, then for any kN and nk+4,

    {1vnvn2,1VnAaVn2,1unmax{1,bBun2,bvkaA(AB)nk1},1Unmax{1,BbUn2,BVkaA(ab)nk1}. (2.6)

    Proof. (1) It follows from (2.2).

    (2) Since ABab1, it follows from (2.2) and (2.3) that for any kN and nk+2,

    un=max{1,bvn1aAUn1}=max{1,baAUn1max{1,abBVn2,vn2ABUn2Vn2}}=max{1,baAUn1,bvn2ABaAUn1Un2Vn2}=max{1,baAUn1,bABaAUn1Un2Vn2max{1,abBVn1,vn3ABUn3Vn3}}=max{1,baAUn1,bvn3(AB)2aAUn1Un2Vn2Un3Vn3}=max{1,baAUn1,bvkaA(AB)nk1Un1Un2Vn2UkVk}.

    In a similar way, also we can obtain the other three formulas.

    (3) By (2.5) one has that for any kN and nk+2,

    {unbaAUn1,UnBaAun1,vnabBVn1,VnAbBvn1,

    from which and (2.4) it follows that for any nk+4,

    {1unmax{1,bBun2,bvkaA(AB)nk1},1Unmax{1,BbUn2,BVkaA(ab)nk1},1vnmax{1,avn2A,vn2}=vn2,1Vnmax{1,AVn2a,Vn2}=AVn2a.

    The proof is complete.

    Proposition 2.2. If ab=AB=1, then {(un,Un,vn,Vn)}+n=1 is eventually periodic with period 2.

    Proof. By the assumption we see a=A and b=B. By (2.5) we see that for any kN and nk+2,

    {un=max{1,b3Un1,b3vkUn1Un2Vn2UkVk},Un=max{1,b3un1,b3Vkun1un2vn2ukvk},vn=max{1,a3Vn1,vkUn1Vn1UkVk},Vn=max{1,a3vn1,Vkun1vn1ukvk}. (2.7)

    (1) If a=b=1, then it follows from (2.7) and (2.4) that for any nk+4,

    {un=max{1,vkUn1Un2Vn2UkVk}max{1,vkUn2Un3Vn3UkVk}=un1,Un=max{1,Vkun1un2vn2ukvk}Un1,vn=max{1,vkUn1Vn1UkVk}vn1,Vn=max{1,Vkun1vn1ukvk}Vn1. (2.8)

    We claim that vn=1 for any n6 or Vn=1 for any n6. Indeed, if vn>1 for some n6 and Vm>1 for some m6, then

    vn=v1Un1Vn1U1V1>1,  Vm=V1um1vm1u1v1>1,

    which implies

    1v1Un1Vn1U1V1V1um1vm1u1v1=Vmvn>1.

    A contradiction.

    If vn=1 for any n6, then by (2.8) we see un=1 for any n10, which implies Un=Vn=V10.

    If Vn=1 for any n6, then by (2.8) we see Un=1 for any n10, which implies vn=un=v10.

    Then, {(un,Un,vn,Vn)}+n=1 is eventually periodic with period 2.

    (2) If a<1<b, then it follows from (2.7) that for any nk+4,

    {un=max{1,b3Un1,b3vkUn1Un2Vn2UkVk},Un=max{1,b3un1,b3Vkun1un2vn2ukvk},vn=max{1,vkUn1Vn1UkVk}vn1,Vn=max{1,Vkun1vn1ukvk}Vn1. (2.9)

    It is easy to verify vn=1 for any n6 or Vn=1 for any n6.

    If Vn=vn=1 eventually, then by (2.9) we have

    {1vkUn1Vn1UkVk eventually,1Vkun1vn1ukvk eventually.

    Since Unb3un1 and unb3Un1, we see

    {un=max{1,b3Un1,b3vkUn1Un2Vn2UkVk}=max{1,b3Un1}un2 eventually,Un=max{1,b3un1,b3Vkun1un2vn2ukvk}=max{1,b3un1}Un2 eventually,

    which implies

    {un2un=max{1,b3Un1}max{1,b3Un3}=un2 eventually,Un2Un=max{1,b3un1}max{1,b3un3}=Un2 eventually.

    If Vn>1=vn eventually, then by (2.9) we have

    {1vkUn1Vn1UkVk eventually,Vn=Vkun1vn1ukvk>1 eventually.

    Thus,

    {un=max{1,b3Un1,b3vkUn1Un2Vn2UkVk}=max{1,b3Un1}un2 eventually,Un=max{1,b3un1,b3Vkun1un2vn2ukvk}=max{1,b3Vkun1un2vn2ukvk}Un2 eventually,

    which implies

    {un2un=max{1,b3Un1}max{1,b3Un3}=un2 eventually,Un=1 eventually  or  b3Vk eventually.

    If Vn=1<vn eventually, then by (2.9) we have Un2=Un eventually and un=un1 eventually. By the above we see that {(un,Un,vn,Vn)}+n=1 is eventually periodic with period 2.

    (3) If b<1<a, then for any kN and nk+2,

    {un=max{1,b3vkUn1Un2Vn2UkVk}un1,Un=max{1,b3Vkun1un2vn2ukvk}Un1,vn=max{1,a3Vn1,vkUn1Vn1UkVk},Vn=max{1,a3vn1,Vkun1vn1ukvk}. (2.10)

    It is easy to verify un=1 for any n3 or Un=1 for any n3.

    If un=Un=1 eventually, then

    {1b3vkUn1Un2Vn2UkVk eventually,1b3Vkun1un2vn2ukvk eventually.

    Thus, by (2.6) we have

    {vn2vn=max{1,a3Vn1,vkUn1Vn1UkVk}=max{1,a3Vn1}vn2 eventually,Vn2Vn=max{1,a3vn1,Vkun1vn1ukvk}=max{1,a3vn1}Vn2 eventually.

    If un=1<Un eventually, then

    {1b3vkUn1Un2Vn2UkVk eventually,1<b3Vkun1un2vn2ukvk=Un eventually.

    Thus,

    {vn2vn=max{1,a3Vn1,vkUn1Vn1UkVk}=max{1,a3Vn1}vn2 eventually,Vn=max{1,a3vn1,Vkun1vn1ukvk}=max{1,Vkun1vn1ukvk}=1 eventually or Vk eventually.

    If un>1=Un eventually, then we have Vn=Vn2 eventually and vn=1 eventually or vn=vk eventually.

    By the above we see that {(un,Un,vn,Vn)}+n=1 is eventually periodic with period 2.

    Proposition 2.3. If ab=1<AB, then {(un,Un,vn,Vn)}+n=1 is eventually periodic with period 2.

    Proof. Note that UnBaAun1 and VnAbBvn1. By (2.5) we see that there exists NN such that for any nN,

    {un=max{1,b2AUn1}un2,Un=max{1,BaAun1,BVkaAun1un2vn2ukvk},vn=max{1,a2BVn1}vn2,Vn=max{1,AbBvn1,Vkun1vn1ukvk}. (2.11)

    It is easy to verify that un=1 for any nN+1 or vn=1 for any nN+1.

    If un=vn=1 eventually, then by (2.11) we see that Un=Un1 eventually and Vn=Vn1 eventually.

    If uM+2n>1=vn eventually for some MN, then by (2.11) and (2.4) we see that

    {uM+2n=b2AUM+2n1>1 eventually,UM+2n+1=max{1,BbUM+2n1,BVkaAuM+2nuM+2n1vM+2n1ukvk}BbUM+2n1 eventually,vn=max{1,a2BVn1}=1 eventually,Vn=max{1,AbBvn1,Vkun1vn1ukvk}Vn1 eventually.

    By (2.11) we see that Un is bounded, which implies B=b.

    If UM+2n1BVkaAuM+2nuM+2n1vM+2n1ukvk eventually, then

    UM+2n+1=BVkaAuM+2nuM+2n1vM+2n1ukvkUM+2n1 eventually.

    Thus, UM+2n+1=UM+2n1 eventually and uM+2n=uM+2n2 eventually. Otherwise, we have UM+2n+1=UM+2n1 eventually and uM+2n=uM+2n2 eventually. Thus, Vn=Vn1=max{1,AbB} eventually since limnVkun1vn1ukvk=0. By (2.2) it follows UM+2n=UM+2n2 eventually and uM+2n+1=uM+2n1 eventually.

    If vM+2n>1=un eventually for some MN, then we may show that {(un,Un,vn,Vn)}+n=1 is eventually periodic with period 2. The proof is complete.

    Proposition 2.4. If ab>1, then {(un,Un,vn,Vn)}+n=1 is eventually periodic with period 2.

    Proof. By (2.5) we see that there exists NN such that for any nN,

    {un=max{1,baAUn1},Un=max{1,BaAun1},vn=max{1,abBVn1},Vn=max{1,AbBvn1}. (2.12)

    If a<A, then for n2k+N with kN,

    vn=max{1,abBVn1}max{1,aAvn2}max{1,(aA)kvn2k},

    which implies vn=1 eventually and Vn=max{1,AbB} eventually.

    If a=A, then

    {vn=max{1,abBVn1}vn2 eventually,Vn=max{1,AbBvn1}Vn2 eventually.

    Which implies

    {vn2vn=max{1,abBVn1}max{1,abBVn3}=vn2 eventually,Vn2Vn=max{1,AbBvn1}max{1,AbBvn3}=Vn2 eventually.

    Thus, Vn,vn are eventually periodic with period 2. In a similar way, we also may show that Un,un are eventually periodic with period 2. The proof is complete.

    From (2.1), (2.2), Proposition 2.1, Proposition 2.2, Proposition 2.3 and Proposition 2.4 one has the following theorem.

    Theorem 2.1. (1) If min{A0C1,B0D1,A1C0,B1D0}<1, then system (1.1) has unbounded solutions.

    (2) If min{A0C1,B0D1,A1C0,B1D0}1, then every solution of system (1.1) is eventually periodic with period 4.

    In this paper, we study the eventual periodicity of max-type system of difference equations of the second order with four variables and period-two parameters (1.1) and obtain characteristic conditions of the coefficients under which every positive solution of (1.1) is eventually periodic or not. For further research, we plan to study the eventual periodicity of more general max-type system of difference equations by the proof methods used in this paper.

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

    Project supported by NSF of Guangxi (2022GXNSFAA035552) and Guangxi First-class Discipline SCPF(2022SXZD01, 2022SXYB07) and Guangxi Key Laboratory BDFE(FED2204) and Guangxi University of Finance and Economics LSEICIC(2022YB12).

    There are no conflict of interest in this article.



    [1] J. Shabbir, S. Gupta, A new estimator of population mean in stratified sampling, Commun. Stat.-Theor. M., 35 (2006), 1201–1209. https://doi.org/10.1080/03610920600629112 doi: 10.1080/03610920600629112
    [2] N. Koyuncu, C. Kadilar, Family of estimators of population mean using two auxiliary variables in stratified random sampling, Commun. Stat.-Theor. M., 38 (2009), 2398–2417. https://doi.org/10.1080/03610920802562723 doi: 10.1080/03610920802562723
    [3] N. Koyuncu, C. Kadilar, On improvement in estimating population mean in stratified random sampling, J. Appl. Stat., 37 (2010), 999–1013. https://doi.org/10.1080/02664760903002675 doi: 10.1080/02664760903002675
    [4] N. Ali, I. Ahmad, M. Hanif, U. Shahzad, Robust-regression-type estimators for improving mean estimation of sensitive variables by using auxiliary information, Commun. Stat.-Theor. M., 50 (2021), 979–992. https://doi.org/10.1080/03610926.2019.1645857 doi: 10.1080/03610926.2019.1645857
    [5] S. Gupta, J. Shabbir, On improvement in estimating the population mean in simple random sampling, J. Appl. Stat., 35 (2008), 559–566. https://doi.org/10.1080/02664760701835839 doi: 10.1080/02664760701835839
    [6] H. P. Singh, G. K. Vishwakarma, A general procedure for estimating the population mean in stratified sampling using auxiliary information, Metron, 68 (2010), 47–65. https://doi.org/10.1007/BF03263523 doi: 10.1007/BF03263523
    [7] H. P. Singh, R. S. Solanki, Efficient ratio and product estimators in stratified random sampling, Commun. Stat.-Theor. M., 42 (2013), 1008–1023. https://doi.org/10.1080/03610926.2011.592257 doi: 10.1080/03610926.2011.592257
    [8] R. S. Solanki, H. P. Singh, An improved estimation in stratified random sampling, Commun. Stat.-Theor. M., 45 (2016), 2056–2070. https://doi.org/10.1080/03610926.2013.826367 doi: 10.1080/03610926.2013.826367
    [9] J. H. Schuenemeyer, L. J. Drew, Statistics for earth and environmental scientists, John Wiley & Sons, 2011. https://doi.org/10.1002/9780470650707
    [10] W. G. Cochran, Sampling techniques, John Wiley & Sons, 1977.
    [11] S. Bahl, R. Tuteja, Ratio and product type exponential estimators, J. Inform. Optim. Sci., 12 (1991), 159–164. https://doi.org/10.1080/02522667.1991.10699058 doi: 10.1080/02522667.1991.10699058
    [12] B. V. S. Sisodia, V. K. Dwivedi, Modified ratio estimator using coefficient of variation of auxiliary variable, J.-Indian Soc. Agr. Stat., 1981.
    [13] C. Kadilar, H. Cingi, Ratio estimators in stratified random sampling, Biometrical J., 45 (2003), 218–225. https://doi.org/10.1002/bimj.200390007 doi: 10.1002/bimj.200390007
    [14] L. N. Upadhyaya, H. P. Singh, Use of transformed auxiliary variable in estimating the finite population mean, Biometrical J., 41 (1999), 627–636. https://doi.org/10.1002/(SICI)1521-4036(199909)41:5<627::AID-BIMJ627>3.0.CO;2-W doi: 10.1002/(SICI)1521-4036(199909)41:5<627::AID-BIMJ627>3.0.CO;2-W
    [15] B. V. S. Sisodia, V. K. Dwivedi, Modified ratio estimator using coefficient of variation of auxiliary variable, J.-Indian Soc. Agr. Stat., 1981.
    [16] M. K. Chaudhary, R. Singh, R. K. Shukla, M. Kumar, F. Smarandache, A family of estimators for estimating population mean in stratified sampling under nonresponse, Pak. J. Stat. Oper. Res., 2009. 47–54. https://doi.org/10.18187/pjsor.v5i1.153 doi: 10.18187/pjsor.v5i1.153
    [17] C. Kadilar, H. Cingi, Improvement in estimating the population mean in simple random sampling, Appl. Math. Lett., 19 (2006), 75–79. https://doi.org/10.1016/j.aml.2005.02.039 doi: 10.1016/j.aml.2005.02.039
    [18] R. Singh, Improved exponential estimator in stratified random sampling, Pak. J. Stat. Oper. Res., 2009, 67–82. https://doi.org/10.18187/pjsor.v5i2.118 doi: 10.18187/pjsor.v5i2.118
    [19] A. C. Onyeka, A class of product-type exponential estimators of the population mean in simple random sampling scheme, Stat. Transit. New Seri., 14 (2013), 189–200. https://doi.org/10.59170/stattrans-2013-012 doi: 10.59170/stattrans-2013-012
    [20] H. P. Singh, R. Tailor, S. Singh, J. M. Kim, A modified estimator of population mean using power transformation, Stat. Pap., 49 (2008), 37–58. https://doi.org/10.1007/s00362-006-0371-2 doi: 10.1007/s00362-006-0371-2
    [21] Ö. Z. E. L. Gamze, Modified exponential type estimator for population mean using auxiliary variables in stratified random sampling, Alphanumeric J., 3 (2015), 49–56. https://doi.org/10.17093/aj.2015.3.2.5000145484 doi: 10.17093/aj.2015.3.2.5000145484
    [22] N. Koyuncu, Efficient estimators of population mean using auxiliary attributes, Appl. Math. Comput., 218 (2012), 10900–10905. https://doi.org/10.1016/j.amc.2012.04.050 doi: 10.1016/j.amc.2012.04.050
    [23] N. Koyuncu, Improved exponential type estimators for finite population mean in stratified random sampling, Pak. J. Stat. Oper. Res., 2016,429–441. https://doi.org/10.18187/pjsor.v12i3.1172 doi: 10.18187/pjsor.v12i3.1172
    [24] K. K. Tiwari, S. Bhougal, S. Kumar, A general class of estimators in stratified random sampling, Commun. Stat.-Simul. C., 52 (2023), 442–452. https://doi.org/10.1080/03610918.2020.1859537 doi: 10.1080/03610918.2020.1859537
    [25] M. Javed, M. Irfan, S. H. Bhatti, R. Onyango, A simulation-based study for progressive estimation of population mean through traditional and nontraditional measures in stratified random sampling, J. Math., 2021, 1–16. https://doi.org/10.1155/2021/9038126 doi: 10.1155/2021/9038126
    [26] S. Muneer, J. Shabbir, A. Khalil, Estimation of finite population mean in simple random sampling and stratified random sampling using two auxiliary variables, Commun. Stat.-Theor. M., 46 (2017), 2181–2192. https://doi.org/10.1080/03610926.2015.1035394 doi: 10.1080/03610926.2015.1035394
    [27] A. Haq, M. Usman, M. Khan, Estimation of finite population variance under stratified random sampling, Commun. Stat.-Simul. Comput., 52 (2023), 6193–6209. https://doi.org/10.1080/03610918.2021.2009866 doi: 10.1080/03610918.2021.2009866
    [28] J. Shabbir, S. Gupta, R. Onyango, On using the conventional and nonconventional measures of the auxiliary variable for mean estimation, Math. Probl. Eng., 2021, 1–13. https://doi.org/10.1155/2021/3741620 doi: 10.1155/2021/3741620
    [29] U. Daraz, J. Shabbir, H. Khan, Estimation of finite population mean by using minimum and maximum values in stratified random sampling, J. Mod. Appl. Stat. Method., 17 (2018), 20. https://doi.org/10.22237/jmasm/1532007537 doi: 10.22237/jmasm/1532007537
    [30] C. Kadilar, H. Cingi, A new ratio estimator in stratified random sampling, Commun. Stat.-Theor. Meth., 34 (2005), 597–602. https://doi.org/10.1081/STA-200052156 doi: 10.1081/STA-200052156
    [31] S. Choudhury, B. K. Singh, An efficient class of dual to product-cum-dual to ratio estimators of finite population mean in sample surveys, Global J. Sci. Front. Res., 12 (2012), 25–33.
  • Reader Comments
  • © 2025 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(506) PDF downloads(53) Cited by(0)

Figures and Tables

Figures(2)  /  Tables(6)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog