P. Borkowski, J. Mielniczuk (2009) Post model-selection estimators of
variance function for non-linear autoregression,Journal of Time Series Analysis, to appear,
pdf
J. Mielniczuk, Z. Zhou, W.B. Wu (2009). On nonparametric prediction of
linear processes, Journal of Time Series Analysis, to appear, pdf
J. Mielniczuk, M. Wojtys (2009). Estimation of Fisher information using
model selection, Metrika, xx-xx, pdf
A. Bryk, J. Mielniczuk, (2008). Using randomization to improve performance
regression estimates under dependence, Acta Scientiarum Mathematicarum (Szeged),
73, 817--838 pdf
J. Mielniczuk, P. Wojdyllo, (2007) Decorrelation of wavelet coefficients for
long-range dependent processes, IEEE Information Theory , 53, 1879-1883
pdf
J. Mielniczuk, P. Wojdyllo, (2007) Estimation of the Hurst exponent
revisited, Computational Statistics & Data Analysis , 51, 4510-4525
pdf
A. Bryk, J. Mielniczuk, (2007) Randomized fixed design regression under
long-range dependent errors , Communications in Statistics, Theory and
Methods 37 ,520--531, pdf
J. Mielniczuk, P. Wojdyllo, (2005) Wavelets for time series data: review and
new results, Control & Cybernetics , 34, 1-31 pdf
A. Bryk, J. Mielniczuk, (2005) Asymptotic properties of kernel density
estimates for linear processes: application of projection method.
Nonparametric Statistics , 14, 121-133 pdf
Mielniczuk, J. and Wu, W.B., (2004) On random-design model with dependent
errors. Statistica Sinica , 14, 1105-1126 pdf
Rekawek, J., Miszczak-Knecht, M., Kawalec, W., Mielniczuk, J. (2003). Heart
variability in healthy children. Folia Cardiologica , 10, 203-211
Wu, W.B., Mielniczuk, J. (2002). Kernel density estimation for linear
proceses. Annals of Statistics , 30, 1441-1459 pdf
Mielniczuk, J. (2002). Some remarks on the almost sure Central Limit Theorem
for dependent sequences. in Limit Theorems in Probability and Statistics II
I. Berkes, E. Csaki, M. Csorgo, eds., 391-403, Bolyai Institute
Publications, Budapeszt
Cwik, J. and Mielniczuk, J. (2001). On construction of confidence intervals
for a mean of dependent data. Discussiones Mathematicae. Probability and
Statistics. 21, 121-147.
Csorgo, S. and Mielniczuk, J. (2000). The smoothing dichotomy in
random-design regression with long-memory errors based on moving averages .
Statistica Sinica vol. 10, pp. 771-787
Cwik, J., Koronacki, J. and J. Mielniczuk Testing for a difference between
conditional variance functions of nonlinear time series, Control &
Cybernetics, vol. 29 , 33-50 (for abstract and introduction click here).
Mielniczuk, J. (2000). Some properties of random stationary sequences with
bivariate densities having diagonal expansions and nonparametric estimators
based on them Journal of Nonparametric Statistics vol. 12, 223-243 pdf
Masry, E. and Mielniczuk, J. (1999). Local linear regression estimation for
time series with long-range dependence Stochastic Processes and Their
Applications vol. 82 , 173-194 pdf
L. Gajek and Mielniczuk, J. (1999). Long- and short-range dependent
sequences under exponential subordination. Statistics and Probability Letters
vol. 43, 113-122 pdf
Csorgo, S. and Mielniczuk, J. (1999). Random-design regression under
long-range dependent errors. Bernoulli vol. 5, 209-224
J. Mielniczuk (1997). Short-range and long-range dependence sums for
infinite-order moving averages and regression estimation, Acta Scientiarum
Mathematicarum (Szeged) vol. 67, 301-316
J. Mielniczuk (1997). On the asymptotic mean integrated squared error of a
kernel density estimator for dependent data, Statistics & Probability
Letters vol. 34, 53-58 pdf
Csorgo, S. and Mielniczuk, J. (1996). The empirical process of a short-range
dependent stationary sequence under Gaussian subordination. Probability
Theory and Related Fields vol. 104, 15-25
Csorgo, S. and Mielniczuk, J. (1995). Extreme values of derivatives of
smoothed fractional Brownian motions. Probability and Mathematical Statistics
vol. 16, 211-219
Hossjer, O. and Mielniczuk, J. (1995). Delta-method for long-range dependent
observations. Journal of Nonparametric Statistics , vol. 5, 75-82.
Csorgo, S. and Mielniczuk, J. (1995). Close short-range dependent sums and
regression estimation. Acta Scientiarum Mathematicarum (Szeged) vol. 60,
177-196.
Csorgo, S. and Mielniczuk, J. (1995). Distant long-range dependent sums with
application to regression estimation. Stochastic Processes & their
Applications vol. 59, 143-155 pdf
Csorgo, S. and Mielniczuk, J. (1995). Nonparametric regression under
long-range dependent normal errors. Annals of Statistics vol. 23,
1000-1014.
Csorgo, S. and Mielniczuk, J. (1995). Density estimation under long-range
dependence. Annals of Statistics vol. 23, 990-999
Gijbels, I. and Mielniczuk, J. (1995). Rates of uniform strong consistency
for grade estimates of a Radon-Nikodym derivative. Statistica Sinica vol.
5, 261-278.
Cwik, J. and Mielniczuk, J. (1995). A nonparametric rank discrimination
method. Computational Statistics & Data Analysis vol. 19, 59-74 .
Mielniczuk, J. and Tyrcha, J. (1993). Strong consistency of multilayer
perceptron regression estimate. Neural Networks vol. 6, 1019-1022
Cwik, J. and Mielniczuk, J. (1993). Data-dependent bandwidth choice for a
grade density kernel estimate. Statistics & Probability Letters vol.
16, 397-405.
Mielniczuk, J. (1992). Grade estimation of Kullback-Leibler information
number. Probability and Mathematical Statistics vol. 13, 139-147.
Mielniczuk, J. (1991). Some asymptotic properties of nonparametric
regression estimators in case of censored data. Statistics vol. 22,
85-93.
Cwik, J. and Mielniczuk, J. (1990). Some topics in estimation of
Neyman-Pearson and performance curves. In Proceedings of the Conference on
Stochastic Methods in Experimental Sciences COSMEX'89, September 1989,
Szklarska Poreba, World Scientific, 114-129.
Gijbels, J. i Mielniczuk, J. (1990). Estimation of the density of a copula
function. Communications in Statistics, Ser. A vol.19, 445-464.
Mielniczuk, J. (1990). Remark concerning data dependent bandwidth choice for
density estimation. Statistics & Probability Letters 9, 27-33.
Cwik, J. i Mielniczuk, J. (1989). Estimation of density ratio with
application to discriminant analysis. Communications in Statistics, Ser. A
vol. 18, 3057-3069.
Mielniczuk, J., Sarda, P. and Vieu, P. (1989). Local data driven bandwidth
choice for density estimation. Journal of Statistical Planning and Inference
vol. 23, 53-69.
Bretagnolle, J. i Mielniczuk, J. (1988). On asymptotic minimaxity of the
adaptive kernel estimate of a density function. Annales d'Institut Henri
Poincare vol. 15, 143-153.
Csorgo, S. and Mielniczuk, J. (1988). Density estimation of the proportional
hazards model. Statistics & Probability Letters vol. 6, 419-426.
Mielniczuk, J. (1987). A remark concerning strong uniform consistency of the
conditional Kaplan-Meier estimator. Statistics & Probability Letters
vol. 5, 333-337.
Mielniczuk, J. (1987). Asymptotic confidence bands for densities based on
nearest neighbor estimators under censoring. Statistics & Probability
Letters vol. 5, 125-128.
Mielniczuk, J. and Kowalczyk, T. (1987). A screening method for a
nonparametric model. Statistics & Probability Letters vol. 5,
163-167.
Mielniczuk, J. (1986). Przyklady modelowania matematycznego w archeologii. W
W. Hensel, G. Donato, S. Tabaczynski, wyd., {/it Teoria i praktyka badan
archeologicznych.} Vol. I. Ossolineum, pp. 329-361. Italian translation in:
Teoria e practica della ricerca archeologica. I. Premesse
metodologische . Il Quadrante Edizioni, str. 325-351.
Mielniczuk, J. (1986). Some asymptotic properties of kernel estimators of a
density function in case of censored data. , Annals of Statistics ,
vol. 14, 767-773.
Mielniczuk, J. (1985). Note on estimation of number of errors in case of
repetitive quality control. Probability and Mathematical Statistics vol.
6, 131-137.
Mielniczuk, J. (1985). Properties of the kernel estimators and of the
adapted Loftsgarden-Quesenberry estimator of a density function for censored
data. Periodica Mathematica Hungarica} vol. 16, 69-81.
Books:
J. Koronacki and J. Mielniczuk Statystyka dla studentow kierunkow
technicznych i przyrodniczych (spis tresci oraz
przedmowa; a textbook in Polish on Statistics for Engineering and the
Sciences), WNT, Warsaw, 2009, 492 pp. (fourth edition, 1st edition was published in 2001)
J. Cwik and J. Mielniczuk
Statystyczne systemy uczace sie - cwiczenia w oparciu o pakiet R
( spis tresci oraz
przedmowa ), Oficyna Wydawnicza PW, Warszawa, 2009, 192 pp.