Wkład Polaków w rozwój statystyki matematycznej i stosowanej po drugiej wojnie światowej

• Authors: Jan Mielniczuk

Title variants

EN

The Contribution of Poles to the Development of Mathematical and Applied Statistics after the Second World War

• Languages of publication: PL
• Publisher: Główny Urząd Statystyczny
• Journal: Przegląd Statystyczny
• Year: 2013
• Volume: 60
• Issue: 1
• Pages: 109-120

Contributors

author

Jan Mielniczuk

• Instytut Podstaw Informatyki PAN, Ul. Jana Kazimierza 5, 01-248 Warszawa
• Politechnika Warszawska, Pl. Politechniki 1, 00-661 Warszawa

References

• Baksalary J., Kala R., (1981), Linear Transformations Preserving Best Linear Unbiased Estimators in a General Gauss-Markoff Model, Ann. Statist., 9, 913–916.
• Bartoszewicz J., (1998), Characterizations of the Dispersive Order of Distributions by the Laplace Transform, Stat. Probab. Letters, 40, 23–29.
• Bartoszyński R., (1972), Model of Circulation and Exchange of Banknotes, Appl. Math., 13, 139–151.
• Bartoszyński R., (1974), On a Metric Structure Derived from Subjective Judgments: Scaling under Perfect and Imperfect Discrimination, Econometrica, 42, 55–71.
• Bartoszyński R., McBride C., Brown B., Thompson J., (1981), Some Nonparametric Techniques for Estimating the Intensity Function of a Cancer Related Nonstationary Poisson Process, Ann. Statist., 9, 150–160.
• Bartoszyński R., Pleszczyńska E., (1980), Reducability of Statistical Structures and Decision Problems, Banach Center Publications, 6, 29–36.
• Bednarski T., (1982), Binary Experiments, Minimax Tests and 2-Alternating Capacities, Ann. Statist., 10, 226–232.
• Bednarski T., (1993), Robust Estimation in the Cox Regression Model, Scandinavian Journal of Statistics, 20, 213–225.
• Bednarski T., (2004), Robust Estimation in the Generalized Poisson Model, Statistics, 38, 149–159.
• Bednarski T., Zontek S., (1996), Robust Estimation of Parameters in Mixed Unbalanced Models, Ann. Statist., 24, 1493–1510.
• Bogdan M., Chakraborti A., Frommlet F., Ghosh J., (2012), Asymptotic Bayes Optimality under Sparsity of Some Multiple Testing Procedures, Ann. Statist., 39, 1551–1579.
• Bogdan M., Ghosh J., Doerge R., (2004), Modifying the Schwarz Bayesian Information Criterion to Locate Multiple Interacting Quantitative Trait Loci, Genetics, 167, 989 999.
• Brown L., Gajek L., (1990), Information Inequalities for the Bayes Risk, Ann. Statist., 18, 1578–1594.
• Caliński T., (2012), Rozwój i osiągnięcia w biometrii polskiej, Przegląd Statystyczny, Numer specjalny 1, 47-52.
• Caliński T., Harabasz J., (1974), Dendrite Method for Cluster Analysis, Comm. Statist. Sim. Comp., 3, 1–27.
• Csörgő S., Mielniczuk J., (1995a), Density Estimation under Long-Range Dependence, Ann. Statist., 23, 990–999.
• Csörgő S., Mielniczuk J., (1995b), Nonparametric Regression under Long-Range Dependence, Ann. Statist., 23, 1000–1014.
• Dalenius T., Hájek J., Zubrzycki S., (1961), On Plane Sampling and Related Geometrical Problems, Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, I, 125–150.
• Dramiński M., Rada-Iglesias A., Enroth S., Wadelius C., Komorowski J., Koronacki J., (2008), Monte-Carlo Feature Selection for Supervised Classification., Bioinformatics, 24, 110 117.
• Ducharme G., Ledwina T., (2003), Efficient and Adaptive Nonparametric Tests for Two-Sample Problem, Ann. Statist., 31, 2036–2058.
• Farrell R., Klonecki W., Zontek S., (1984), All Admissible Linear Estimators of the Vector of Gamma Scale Parameters with Application to Random Effects Models, Ann. Statist., 12, 261-281.
• Fisz M., (1954), Rachunek Prawdopodobieństwa i Statystyka Matematyczna, PWN, Warszawa.
• Gajek L., (1986a), Estimating a Density and its Derivatives via the Minimum Distance Method, Probability Theory and Related Fields, 80, 601–617.
• Gajek L., (1986b), On Improving Density Estimators which Are Not Bona Fide Densities, Ann. Statist., 14, 1612–1618.
• Gajek L., Rychlik T., (1998), Projection Method for Moment Bounds on Order Statistics from
• Restricted Families. II. Independent Case, J. Multivar. Anal., 31, 156–182.
• Gnot S., (1983), Bayes Estimation in Linear Models: Coordinate Free Approach, J. Mult. Anal., 13, 40–51.
• Gnot S., Kleffe J., Zmyślony R., (1985), Nonnegativity of Admissible Invariant Estimates in Linear Models with Two Variance Components, J. Statist. Plann. Inference, 12, 249–258.
• Gnot S., Ledwina T., (1980), Testing for Hardy-Weinberg Equilibrium, Biometrics, 36, 161–175.
• Greblicki W., Krzyzak M., Pawlak M., (1984), Distribution-Free Pointwise Consistency of Kernel Regression Estimate, Ann. Statist., 12, 1570–1575.
• Inglot T., Ledwina T., (1996), Asymptotic Optimality of Data Driven Neyman’s Tests for Uniformity, Ann. Statist., 24, 1982–2019.
• Kallenberg W., Ledwina T., (1997), Data Driven Smooth Tests when the Hypothesis is Composite, J. Amer. Statist. Assoc., 92, 1094–1104.
• Klonecki W., (1977), Optimal C(α) Tests for Homogeneity, Proceedings of the Symposium to Honour J. Neyman, 161–175.
• Klonecki W., (1995), Jerzy Neyman (1894-1981), Probabillity and Mathematical Statistics, 15, 7–14.
• Klonecki W, Zonn W., (1973), Jerzy Spława-Neyman, Wiadomości Matematyczne, XVI, 53–70.
• Koronacki J., Wertz W., (1988), A Global Stopping Rule for Recursive Density Estimators, J. Statist. Plann. Inference, 20, 23–39.
• Koronacki S., Lasota K., Niemiro W., (2005), Positron Emission Tomography by Markov Chain Monte Carlo with Auxiliary Variables, Pattern Recognition, 38, 241–250.
• Kowalczyk T., Kowalski A., Matuszewski A, Pleszczynska E., (1979), Screening and Monotonic Dependence Functions in the Multivariate Case, Ann. Statist., 7, 607–614.
• Kowalczyk T., Pleszczynska E., (1977), Monotonic Dependence Functions of Bivariate Distributions, Ann. Statist., 5, 1221–1227.
• Kozek A., (1982a), Efficiency and Cramér-Rao Bounds for Convex Loss Functions, J. Mult. Analysis, 12, 89–106.
• Kozek A., (1982b), Towards Calculus of Admissibility, Ann. Statist., 10, 825–837.
• Krzyśko M., (1983), Asymptotic Distribution of the Discriminant Function, Stat. Prob. Letters, 1, 243–250.
• Krzyśko M., Wołyński W., (2009), New Variants of Pairwise Classification, European J. Operational Research, 199, 512–519.
• Łatuszyński K., Niemiro W., (2011), Rigorous Confidence Bounds for MCMC under a Geometric Drift Condition, J. Complexity, 27, 23–38.
• Ledwina T., (1994), Data Driven Version of the Neyman Smooth Test of Fit, J. Amer. Statist. Assoc., 89, 1000–1005.
• Ledwina T., (2012), Jerzy Neyman (1894-1981), Statistics in Transition - New Series, 13, 169–178.
• Ledwina T., Wyłupek G., (2012), Two-Sample Test Against One-Sided Alternatives, Scand. J. Statist., 39, 758–781.
• Lenart Ł., Leskow J, Synowiecki R., (2008), Subsampling in Estimation of Autocovariance of PC Time Series, J. Time Series Analysis, 29, 995–1018.
• Łukaszewicz J., (1967), Julian Perkal (1913-1965), Wiadomości Matematyczne, X, 29¬ 36.
• Łukaszewicz J., Sadowski S., (1960), On Comparing Several Populations with a Control Population, Zastosow. Mat., 5, 309–320.
• Magiera R., (1987), Admissible Sequential Polynomial Estimators for Stochastic Processes, Sequential Analysis, X, 147–167.
• Mielniczuk J. Zhou Z., Wu W., (2010), On Nonparametric Prediction of Linear Processes, J. Time Series Analysis, 30, 652–673.
• Mielniczuk J., (1986), Some Asymptotic Properties of Kernel Estimators of a Density Function in Case of Censored Data, Ann. Statist., 14, 1136–1139.
• Musiela M., (1981), On Sequential Estimation of Parameters of Continuous Gaussian Markov Processes, Probability and Mathematical Statistics, 2, 37–53.
• Niemiro W., Pokarowski P., (2009), Fixed Precision MCM Estimation by Median of Products of Averages, J. Appl. Probab., 46, 309–329.
• Pokarowski P., Kloczkowski A., Jernigan R., Kothari N., Pokarowska M., Koliński A., (2005), Inferring Ideal Amino Acids Interaction Forms from Statistical Protein Contact Potentials, PROTEINS: Structure, Function and Bioinformics, 59, 49–57.
• Rychlik T., (1994), Distributions and Expectations of Order Statistics from Possibly Dependent Samples, J. Mult. Anal., 48, 31–42.
• Rychlik T., (2001), Projecting Statistical Functionals, Lecture Notes in Statistics 160, Springer, New York.
• Różański R., Zagdański A., (2006), Estimation of the Drift Function for Ito Processes and Some Class of Semimartingales via Histogram Sieve, Appl. Math., 33, 21–40.
• Steinhaus H., (1957), The Problem of Estimation, Ann. Math. Statist., 28, 633–648.
• Stępniak C., Wong S., Wu J., (1984), Comparison of Linear Experiments with Known Covariances, Ann. Statist., 12, 358–365.
• Szkutnik Z., (1988), Most Powerful Invariant Tests for Binormality, Ann. Statist., 16, 292–301.
• Szkutnik Z., (2000), Unfolding Intensity Function of a Poisson Process in Models with Approximately Specified Folding Operator, Metrika, 52, 11–26.
• Szkutnik Z., (2003), Doubly Smoothed EM Algorithm for Statistical Inverse Problems, J. Amer. Statist. Assoc., 98, 178–192.
• Trybuła S., (1958), Some Problems of Simultanous Minimax Estimation, Ann. of Math. Statist., 29, 245–253.
• Zielinski R., (1983), Robust Statistical Procedures: A General Approach, Lecture Notes in Statistics, 28, 285–295.
• Zmyślony R., (1980), A Characterization of Best Linear Unbiased Estimators in the General
• Linear Model, Lecture Notes in Statistics, 2, 365–378.
• Zubrzycki S., (1957), O szacowaniu parametrów złóż geologicznych, Zastosowania Matematyki, 3, 105–153.
• Zubrzycki S., (1966), Wykłady z Rachunku Prawdopodobieństwa i Statystyki Matematycznej, PWN, Warszawa.