Free Access
Issue
RAIRO-Oper. Res.
Volume 55, Number 2, March-April 2021
Page(s) 979 - 996
DOI https://doi.org/10.1051/ro/2021051
Published online 07 May 2021
  • S. Baillargeon and L. Rivest, The construction of stratified designs in R with the package stratification. Surv. Methodol. 37 (2011) 53–65. [Google Scholar]
  • M. Ballin and G. Barcaroli, Joint determination of optimal stratification and sample allocation using genetic algorithm. Surv. Methodol. 39 (2013) 369–393. [Google Scholar]
  • J.A.M. Brito, L. Ochi, F.M.T. Montenegro and N. Maculan, An iterative local search approach applied to the optimal stratification problem. Int. Trans. Oper. Res. 17 (2010) 753–764. [Google Scholar]
  • J.A.M. Brito, P.L.N. Silva, G.S. Semaan and N. Maculan, Integer programming formulations applied to optimal allocation in stratified sampling. Surv. Methodol. 41 (2015) 427–442. [Google Scholar]
  • J. Brito, G. Semaan, A. Fadel and L. Brito, An optimization approach applied to the optimal stratification problem. Commun. Stat. Simul. Comput. 46 (2017) 4491–4451. [Google Scholar]
  • J. Brito, T. Veiga and P. Silva, An optimisation algorithm applied to the one-dimensional stratification problem. Surv. Methodol. 45 (2019) 295–315. [Google Scholar]
  • R. Chambers and R. Dunstan, Estimating distribution functions from survey data. Biometrika 73 (1986) 597–604. [CrossRef] [MathSciNet] [Google Scholar]
  • W.G. Cochran, Samppling Techniques, 3rd edition. Wiley Series in Probability and Statistics (2007). [Google Scholar]
  • T. Dalenius, The problem of optimum stratification. Skandinavisk Aktuarietidskrift 1950 (1950) 203–213. [Google Scholar]
  • T. Dalenius and J. Hodges, Minimum variance stratification. J. Am. Stat. Assoc. 285 (1959) 88–101. [Google Scholar]
  • F. Danish, A mathematical programming approach for obtaining optimum strata boundaries using two auxiliary variables under proportional allocation. Stat. Trans. New Ser. 19 (2018) 507–526. [Google Scholar]
  • F. Danish and S. Rizvi, Optimum stratification in bivariate auxiliary variables under neyman allocation. J. Mod. Appl. Stat. Methods 17 (2018) 2–24. [Google Scholar]
  • F. Danish, S. Rizvi, M. Jeelani and J. Reshi, Obtaining strata boundaries under proportional allocation with varying cost of every unit. Pak. J. Stat. Oper. Res. 13 (2017) 567. [Google Scholar]
  • F. Danish, S. Rizvi, M.K. Sharma, M.I. Jeelani, B. Kumar and Q.F. Dar, Optimum stratification for two stratifying variables. Rev. Invest. Oper. 40 (2019) 562–573. [Google Scholar]
  • G. Ekman, An approximation useful in univariate stratification. Ann. Math. Stat. 30 (1959) 219–229. [Google Scholar]
  • G. Glasser, On the complete coverage of large units in a statistical study. Rev. Int. Stat. Inst. 30 (1962) 28–32. [Google Scholar]
  • F. Glover and G.A. Kochenberger, Handbook of Metaheuristics. Springer (2003). [Google Scholar]
  • P. Gunning and J.M. Horgan, A new algorithm for the construction of stratum boundaries in skewed populations. Surv. Methodol. 30 (2004) 159–166. [Google Scholar]
  • J. Han, M. Kamber and J. Pei, Data Mining: Concepts and Techniques, 3rd edition. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (2011). [Google Scholar]
  • P. Hansen and N. Mladenović, Variable neighborhood search: principles and applications. Eur. J. Oper. Res. 130 (2001) 449–467. [Google Scholar]
  • P. Hansen, N. Mladenović and D. Perez-Brito, Variable neighborhood decomposition search. J. Heuristics 7 (2001) 335–350. [CrossRef] [Google Scholar]
  • D. Hedlin, A procedure for stratification by an extended Ekman rule. J. Official Stat. 16 (2000) 15–29. [Google Scholar]
  • M.A. Hidiroglou, The construction of a self-representing stratum of large units in survey design. Am. Stat. 40 (1986) 27–31. [Google Scholar]
  • M. Hidiroglou and M. Kozak, Stratification of skewed populations: a comparison of optimisation-based versus approximate methods. Int. Stat. Rev. 86 (2018) 87–105. [Google Scholar]
  • T. Keskintürk and S. Er, A genetic algorithm approach to determine stratum boundaries and sample sizes of each stratum in stratified sampling. Comput. Stat. Data Anal. 52 (2007) 53–67. [Google Scholar]
  • M. Khan, N. Nand and N. Ahmad, Determining the optimum strata boundary points using dynamic programming. Surv. Methodol. 34 (2008) 205–214. [Google Scholar]
  • L. Kish, Survey Sampling. Wiley New York, Chichester (1965). [Google Scholar]
  • M. Kozak, Optimal stratification using random search method in agricultural surveys. Stat. Trans. 6 (2004) 797–806. [Google Scholar]
  • M. Kozak, Multivariate sample allocation: application of a random search method. Stat. Trans. 7 (2006) 889–900. [Google Scholar]
  • M. Kozak, Comparison of random search method and genetic algorithm for stratification. Commun. Stat. Simul. Comput. 43 (2014) 249–253. [Google Scholar]
  • M. Kozak and M.R. Verma, Geometric versus optimization approach to stratification: a comparison of efficiency. Surv. Methodol. 32 (2006) 157–163. [Google Scholar]
  • M. Kozak, M.R. Verma and A. Zieliński, Modern approach to optimum stratification: review and perspectives. Stat. Trans. 8 (2007) 223–250. [Google Scholar]
  • P. Lavallée and M.A. Hidiroglou, On the stratification of skewed populations. Surv. Methodol. 14 (1988) 33–43. [Google Scholar]
  • B. Lednicki and R. Wieczorkowski, Optimal stratification and sample allocation between subpopulations and strata. Stat. Trans. 6 (2003) 287–305. [Google Scholar]
  • J. Lisic, H. Sang, Z. Zhu and S. Zimmer, Optimal stratification and allocation for the june agricultural survey. J. Official Stat. 34 (2018) 121–148. [Google Scholar]
  • S.L. Lohr, Sampling: Design and Analysis, 2nd edition. Chapman and Hall/CRC (2019). [Google Scholar]
  • D. Rao, M. Khan and K. Reddy, Optimum stratification of a skewed population. Int. J. Math. Comput. Sci. 8 (2014) 492–495. [Google Scholar]
  • K. Reddy and M. Khan, Optimal stratification in stratified designs using weibull-distributed auxiliary information. Commun. Stat. Theory Methods 48 (2019) 3136–3152. [Google Scholar]
  • K. Reddy and M. Khan, stratifyR: an R package for optimal stratification and sample allocation for univariate populations. Aust. New Zealand J. Stat. 62 (2020) 383–405. [Google Scholar]
  • K. Reddy, M. Khan and S. Khan, Optimum strata boundaries and sample sizes in health surveys using auxiliary variables. PLoS ONE 13 (2018) e0194787. [PubMed] [Google Scholar]
  • L. Rivest, A generalization of the Lavallé and Hidiroglou algorithm for stratification in business surveys. Surv. Methodol. 28 (2002) 191–198. [Google Scholar]
  • S. Ross, A First Course in Probability, 10th edition. Pearson (2018). [Google Scholar]
  • V. Sethi, A note on the optimum stratification of populations for estimating the population means. Aust. J. Stat. 5 (1963) 20–33. [Google Scholar]

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