| dc.contributor.author | Baszczyńska, Aleksandra | |
| dc.date.accessioned | 2026-06-22T13:14:45Z | |
| dc.date.available | 2026-06-22T13:14:45Z | |
| dc.date.issued | 2016-12-30 | |
| dc.identifier.citation | Baszczyńska A., Parametr wygładzania w estymacji jądrowej funkcji gęstości dla zmiennych losowych w badaniach ekonomicznych, Wydawnictwo Uniwersytetu Łódzkiego, Łódź 2016, https://doi.org/10.18778/8088-280-5 | pl |
| dc.identifier.isbn | 978-83-8088-279-9 | |
| dc.identifier.uri | http://hdl.handle.net/11089/58623 | |
| dc.description.abstract | Estymacja jądrowa funkcji gęstości jest jedną z podstawowych procedur stosowanych w analizach ekonomicznych, gdyż w sposób jednoznaczny określa zmienną losową utożsamianą w badaniach z cechą statystyczną. W pracy przedstawiono metodę estymacji jądrowej funkcji gęstości, ze szczególnym uwzględnieniem procedur wyboru parametru wygładzania. Za pomocą metod symulacyjnych analizie poddano własności parametrów wygładzania, wyznaczonych omawianymi metodami, uwzględniając zarówno liczebność próby, jak i postać funkcji jądra wykorzystywanej w estymatorze jądrowym funkcji gęstości. Zaproponowano również nową metodę wyboru parametru wygładzania, opartą na średniej harmonicznej, która ze względu na uogólnioną postać średniej charakteryzuje się uniwersalnością w zakresie stosowania tej metody. Uwzględniono przykłady zastosowania w badaniach ekonomicznych prezentowanych metod wyboru parametru wygładzania w procesie estymacji jądrowej funkcji gęstości dla zmiennych losowych. | pl |
| dc.description.abstract | The economic phenomena can be analyzed using the procedures of mathematical statistics. It is closely related to the mass character of the economic phenomena, where a large amount of information makes that, in many cases, it is impossible to use a descriptive statistical analysis effectively. Moreover, the popularity of mathematical statistics is connected with the simplicity and intuitive nature of mathematical statistics procedures. | en |
| dc.language.iso | pl | |
| dc.publisher | Wydawnictwo Uniwersytetu Łódzkiego | pl |
| dc.relation.ispartofseries | Ekonomia | pl |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | parametr wygładzania | pl |
| dc.subject | funkcje jądra | pl |
| dc.subject | estymacja jądrowa | pl |
| dc.subject | zmienne losowe | pl |
| dc.title | Parametr wygładzania w estymacji jądrowej funkcji gęstości dla zmiennych losowych w badaniach ekonomicznych | pl |
| dc.title.alternative | Smoothing Parametr in Kernel Density Estimation for Random Variables in Economic Researches | en |
| dc.type | Book | |
| dc.rights.holder | © Copyright by Aleksandra Baszczyńska, Łódź 2016; © Copyright for this edition by Uniwersytet Łódzki, Łódź 2016 | pl |
| dc.contributor.authorAffiliation | Uniwersytet Łódzki, Wydział Ekonomiczno-Socjologiczny, Katedra Metod Statystycznych | pl |
| dc.identifier.eisbn | 978-83-8088-280-5 | |
| dc.references | Abadir Karim M., Lawford Steve, (2004), Optimal Asymmetric Kernels, „Economics Letters”, 83, 61–68. | pl |
| dc.references | Albers Martina G., (2012), Boundary Estimation of Densities with Bounded Support, www.sam.math.ethz.ch/sfs/research/mas_theses/2012/albers.pdf [30.03.2015]. | pl |
| dc.references | Arbuthnot John, (1710), An Argument for Divine Providence, Taken From the Constant Regularity Observed in the British of Both Sexes, „Philosophical Transactions of the Royal Society of London”, 27, 186–190, doi:10.1098/rstl.1710.0011, http://rstl.royalsocietypublishing.org/content/27/325-336/186 [30.03.2015]. | pl |
| dc.references | Baszczyńska Aleksandra, (2013a), Some Remarks on the Symmetry Kernel Test, „Acta Universitatis Lodziensis. Folia Oeconomica”, 285, 21–29. | pl |
| dc.references | Baszczyńska Aleksandra, (2013b), Uwagi o miarach podobieństwa w jądrowych testach zgodności, [w:] Zbigniew E. Zieliński (red.), Rola informatyki w naukach ekonomicznych i społecznych. Innowacje i implikacje interdyscyplinarne, Wydawnictwo Wyższej Szkoły Handlowej w Kielcach, Kielce, 261–267. | pl |
| dc.references | Baszczyńska Aleksandra, (2014a), Testing Significance of Peaks in Kernel Density Estimator by SiZer Map, [w:] Monika Papież, Sławomir Śmiech (red.), Proceedings of the 8th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena, Foundation of the Cracow University of Economics, Kraków, 2, 9–17. | pl |
| dc.references | Baszczyńska Aleksandra, (2014b), Computer-Assisted Choice of Smoothing Parameter in Kernel Methods Applied in Economic Analysis, [w:] Quantitative Methods in Economics (Metody ilościowe w badaniach ekonomicznych), Warsaw University of Life Sciences Press, Warszawa, XV/2, 37–46. | pl |
| dc.references | Baszczyńska Aleksandra, (2015), Bias Reduction in Kernel Estimator of Density Function in Boundary Region, [w:] Quantitative Methods in Economics (Metody ilościowe w badaniach ekonomicznych), Warsaw University of Life Sciences Press, Warszawa, XVI/1, 7–16. | pl |
| dc.references | Baszczyńska Aleksandra, (2016a), Kernel Estimation of Cumulative Distribution Function for Random Variable with Bounded Support, „Statistics in Transition. New Series”, 17, 3, 541–556. | pl |
| dc.references | Baszczyńska Aleksandra, (2016b), Boundary Effect Reduction in Kernel Estimation of Chosen Functional Characteristics of Random Variable, „Zeszyty Naukowe Wyższej Szkoły Bankowej we Wrocławiu”, 16, 3, 111–121. | pl |
| dc.references | Bickel Peter J., Rosenblatt Murray, (1973), On Some Global Measures of the Deviations of Density Function Estimates, „The Annals of Statistics”, 1, 6, 1071–1095. | pl |
| dc.references | Bickel Peter J., Rosenblatt Murray, (1975), Notes: Corrections to “On Some Global Measures of the Deviations of Density Function Estimates”, „The Annals of Statistics”, 3, 6, 1370. | pl |
| dc.references | Birnbaum Zygmunt Wilhelm, Saunders Sam C., (1969), A New Family of Life Distribution, „Journal of Applied Probability”, 6, 2, 319–327. | pl |
| dc.references | Bowman Adrian W., Azzalini Adelchi, (2004), Applied Smoothing Techniques for Data Analysis, Oxford University Press, Oxford. | pl |
| dc.references | Cao Ricardo, Cuevas Antonio, Manteiga Wensceslao Gonzalez, (1994), A Comparative Study of Several Smoothing Methods in Density Estimation, „Computational Statistics and Data Analysis”, 17, 2, 153–176. | pl |
| dc.references | Cha Sung Hyuk, (2007), Comprehensive Survey on Distance/Similarity Measures between Probability Density Function, „International Journal of Mathematical Models and Methods in Applied Sciences”, 4, 1, 300–307. | pl |
| dc.references | Chacko V. M., Mariya Jeeja P. V., Deepa Paul, (2015), p-Birnbaum Saunders Distribution: Applications to Reliability and Electronic Banking Habits, http://www.gnedenko-forum.org/Journal/2015/012015/RTA_1_2015-07.pdf [15.03.2015]. | pl |
| dc.references | Chen Song Xi, (1999), Beta Kernel Estimators for Density Functions, „Computational Statistics and Data Analysis”, 31, 131–145. | pl |
| dc.references | Chen Song Xi, (2000a), Beta Kernel Smoothers for Regression Curves, „Statistica Sinica”, 10, 73–91. | pl |
| dc.references | Chen Song Xi, (2000b), Probability Density Function Estimation Using Gamma Kernels, „Annals of the Institute of Statistical Mathematics”, 52, 3, 471–480. | pl |
| dc.references | Chiu Shean-Tsong, (1991), Bandwidth Selection for Kernel Density Estimation, „The Annals of Statistics”, 19, 4, 1883–1905. | pl |
| dc.references | Chiu Shean-Tsong, (1996), A Comparative Review of Bandwidth Selection for Kernel Density Estimation, „Statistica Sinica”, 6, 129–145. | pl |
| dc.references | Chmielińska Magdalena, (2014), Zastosowanie estymacji jądrowej do monitorowania procesu o nieznanym rozkładzie, „Studia Ekonomiczne – Zeszyty Naukowe Uniwersytetu Ekonomicznego w Katowicach”, 203, 39–49. | pl |
| dc.references | Cline Daren B. H., (1988), Admissible Kernel Estimators of a Multivariate Density, „The Annals of Statistics”, 16, 4, 1421–1427. | pl |
| dc.references | Czyżycki Rafał, (2013), Estymacja jądrowa w modelowaniu rozkładu stopy zwrotu, „Zeszyty Naukowe Wyższej Szkoły Bankowej w Poznaniu”, 47, 2. | pl |
| dc.references | Devroye Luc, (1989), The Double Kernel Method in Density Estimation, „Annales de L’institut Henri Poincaré (B), Probabilité et Statistiques”, 25, 4, 533–580. | pl |
| dc.references | Devroye Luc, Györfi László, (1985), Nonparametric Density Estimation. The L1 View, John Wiley and Sons, New York. | pl |
| dc.references | Devroye Luc, Lugosi Gábor, (2001), Combinatorial Methods in Density Estimation, Springer-Verlag, New York. | pl |
| dc.references | Díaz-García Josè A., Leiva-Sánchez Victor, (2002), A New Family of Life Distributions Based on Birnbaum-Saunders Distribution, Comunicación Técnica No I-02-17/03-09-2002, (PE/CIMAT), www.cimat.mx/reportes/enlinea/I-02-17.pdf [15.03.2015]. | pl |
| dc.references | Domański Czesław, (1979), Statystyczne testy nieparametryczne, Polskie Wydawnictwo Ekonomiczne, Warszawa. | pl |
| dc.references | Domański Czesław, (1986), Teoretyczne podstawy testów nieparametrycznych i ich zastosowanie w naukach ekonomiczno-społecznych, Wydawnictwo Uniwersytetu Łódzkiego, Łódź. | pl |
| dc.references | Domański Czesław, (1990), Testy statystyczne, Polskie Wydawnictwo Ekonomiczne, Warszawa. | pl |
| dc.references | Domański Czesław, Pekasiewicz Dorota, Baszczyńska Aleksandra, Witaszczyk Anna, (2014), Testy statystyczne w procesie podejmowania decyzji, Wydawnictwo Uniwersytetu Łódzkiego, Łódź. | pl |
| dc.references | Domański Czesław, Pruska Krystyna (2000), Nieklasyczne metody statystyczne, Polskie Wydawnictwo Ekonomiczne, Warszawa. | pl |
| dc.references | Domański Czesław, Pruska Krystyna, Wagner Wiesław, (1998), Wnioskowanie statystyczne przy nieklasycznych założeniach, Wydawnictwo Uniwersytetu Łódzkiego, Łódź. | pl |
| dc.references | Duin Robert P. W., (1976), On the Choice of Smoothing Parameters of Parzen Estimators of Probability Density Functions, IEEE Transactions on Computers, C–25, 1175–1179, rduin.nl/papers/comp_76_parzen.pdf [2.04.2016]. | pl |
| dc.references | Efromovitch Sam, (1999), Nonparametric Curve Estimation: Methods, Theory and Applications, Springer-Verlag, New York. | pl |
| dc.references | Fernandes Marcelo, Monteiro Paulo Klinger, (2005), Central Limit Theorem for Asymmetric Kernel Functionals, „Annals of the Institute of Statistical Mathematics”, 57, 3, 425–442. | pl |
| dc.references | Gajek Lesław, (1986), On Improving Density Estimators are not Bona Fide Functions, „The Annals of Statistics”, 14, 4, 1612–1618. | pl |
| dc.references | Gajek Lesław, Kałuszka Marek, (1996), Wnioskowanie statystyczne. Modele i metody, Wydawnictwa Naukowo-Techniczne, Warszawa. | pl |
| dc.references | Gefeller Olaf, Hjort Nils Lid, (1998), A New Look at the Visual Performance of Nonparametric Hazard Rate Estimators, [w:] I. Balderjahn, R. Mathar, M. Schader (eds.) Classification, Data Analysis, and Data Highways: Proceedings of the 21st Annual Conference of the Gesellschaft für Klassifikation e. V., University of Potsdam, March 12–14, 1997, Springer-Verlag, Berlin. | pl |
| dc.references | Gibbons Jean Dickinson, Chakraborti Subhabrata, (2003), Nonparametric Statistical Inference, Marcel Dekker, Inc., New York, Basel. | pl |
| dc.references | Guidoum Arsalane Chouaib, (2015), Kernel Estimator and Bandwidth Selection for Density and its Derivatives, https://cran.r-project.org/web/packages/kedd/vignettes/kedd.pdf [2.04.2016]. | pl |
| dc.references | Györfi László, Kohler Michael, Krzyżak Adam, Walk Harro, (2002), A Distribution-Free Theory of Nonparametric Regression, Springer-Verlag, New York. | pl |
| dc.references | Hajja Mowaffag, Bullen Peter, S., Matkowski Janusz, Neuman Edward, Simic Slavko, (2013), Means and Their Inequalities, „International Journal of Mathematics and Mathematical Sciences”, Hindawi Publishing Corporation, http://dx.doi.org/10.1155/2013/698906 [2.04.2016]. | pl |
| dc.references | Hall Peter, (1983), Large Sample Optimality of Least Squares Cross-Validation in Density Estimation, „The Annals of Statistics”, 11, 1156–1174. | pl |
| dc.references | Hall Peter, Wand Matthew P., (1988), Minimizing L1 Distance in Nonparametric Density Estimation, „Journal of Multivariate Analysis”, 26, 1, 59–88. | pl |
| dc.references | Hall Peter, Lahiri Soumendra Nath, Truong Young K., (1995), On Bandwidth Choice for Density Estimation with Dependent Data, „The Annals of Statistics”, 23, 6, 2241–2263. | pl |
| dc.references | Hall Peter, Murison Robert D., (1993), Correcting the Negativity of High-Order Kernel Density Estimators, „Journal of Multivariate Analysis”, 47, 103–122. | pl |
| dc.references | Hansen Bruce E., (2005), Exact Mean Integrated Squared Error of Higher Order Kernel Estimators, „Econometric Theory”, 21, 1031–1057. | pl |
| dc.references | Hansen Bruce E., (2009), Lectures Notes on Nonparametric, www.ssc.wisc.edu/~bhansen/718/NonParametrics1.pdf [2.02.2015]. | pl |
| dc.references | Härdle Wolfgang, (1990), Applied Nonparametric Regression, Cambridge University Press, Cambridge. | pl |
| dc.references | Härdle Wolfgang, (1991), Smoothing Techniques With Implementation in S, Springer Series in Statistics, Springer-Verlag, Berlin, Heidelberg. | pl |
| dc.references | Härdle Wolfgang, Marron J. Steve, Wand Matt P., (1990), Bandwidth Choice for Density Derivatives, „Journal of Royal Statistical Society B (Methodological)”, 52, 1, 223–232. | pl |
| dc.references | Härdle Wolfgang, Müller Marlene, Sperlich Stefan, Werwatz Axel, (2004), Nonparametric and Semiparametric Models, Springer Series in Statistics, Springer-Verlag, Berlin, Heidelberg. | pl |
| dc.references | Heidenreich Nils-Bastian, Schindler Anja, Sperlich Stefan, (2013), Bandwidth Selection for Kernel Density Estimation: a Review of Fully Automatic Selectors, „AStA Advances in Statistical Analysis”, 97, 4, 403–433. | pl |
| dc.references | Hirukawa Masayuki, Sakudo Mari, (2014), Nonnegative Bias Reduction Methods for Density Estimation Using Asymmetric Kernels, „Computational Statistics and Data Analysis”, 75, 112–123. | pl |
| dc.references | Hodges Joseph Lawson, Lehmann Erich Leo, (1956), The Efficiency of Some Nonparametric Competitors to the t-test, „The Annals of Mathematical Statistics”, 13, 324–335. | pl |
| dc.references | Horová Ivanka, (2015), Optimization Problems Connected with Kernel Smoothing, http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.412.8628 [20.04.2015]. | pl |
| dc.references | Horová Ivanka, Koláček Jan, Zelinka Jiři, (2012), Kernel Smoothing in MATLAB. Theory and Practice of Kernel Smoothing, World Scientific, New Yersey. | pl |
| dc.references | Horová Ivanka, Zelinka Jiři, (2007), Contribution to the Bandwidth Choice for Kernel Density Estimates, „Computational Statistics”, 22, 1, 31–47. | pl |
| dc.references | Hotelling Harold, Pabst Margaret R., (1936), Rank Correlation and Tests of Significance Involving no Assumption of Normality, „The Annals of Mathematical Statistics”, 7, 29–43. | pl |
| dc.references | Jin Xiaodong, Kawczak Janusz, (2003), Birnbaum-Saunders and Lognormal Kernel Estimators for Modelling Durations in High Frequency Financial Data, „Annals of Economics and Finance”, 4, 103–124. | pl |
| dc.references | Jones M. Chris, (1993), Simple Boundary Correction for Kernel Density Estimation, „Statistics and Computing”, 3, 135–146. | pl |
| dc.references | Jones M. Chris, Foster Peter J., (1996), A Simple Nonnegative Boundary Correction Method for Kernel Density Estimation, „Statistica Sinica”, 6, 1005–1013. | pl |
| dc.references | Jones M. Chris, Marron J. Steve, Park Byeong U., (1991), A Simple Root n Bandwidth Selector, „The Annals of Statistics”, 19, 4, 1919–1932. | pl |
| dc.references | Jones M. Chris, Marron J. Steve, Sheather Simon J., (1996), A Brief Survey of Bandwidth Selection for Density Estimation, „Journal of the American Statistical Association”, 91, 433, 401–407. | pl |
| dc.references | Jones, M. Chris, Signorini David, (1997), A Comparison of Higher-Order Bias Kernel Density Estimators, „Journal of the American Statistical Association”, 92, 439, 1063–1073. | pl |
| dc.references | Karunamuni Rohana J., Alberts Tom, (2005), On Boundary Correction in Kernel Density Estimation, „Statistical Methodology”, 2, 3, 191–212. | pl |
| dc.references | Kile Håkon, (2010), Bandwidth Selection in Kernel Density Estimation, Norwegian University of Science and Technology, Department of Mathematical Sciences, http://www.google.pl/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CCAQFjAA&url=http%3A%2F%2Fwww.diva-portal.org%2Fsmash%2Fget%2Fdiva2%3A348940%2FFULLTEXT01.pdf&ei=2sdHVZKiDeneywPO44HoCg&usg=AFQjCNFlj5j4JUc2ifE058XO1xSQsRPTIA&bvm=bv.92291466,d. bGQ [20.01.2015]. | pl |
| dc.references | Kim Choongrak, Kim Woochul, Park Byeong U., (2003), Skewing and Generalized Jackknifing in Kernel Density Estimation, „Communications in Statistics. Theory and Practice”, 32, 11, 2153–2162. | pl |
| dc.references | Koláček Jan, Poměnková Jitka, (2006), A Comparative Study of Boundary Effects for Kernel Regression, „Austrian Journal of Statistics”, 35, 2&3, 281–288. | pl |
| dc.references | Kończak Grzegorz, (2013), O pewnej konstrukcji przedziałów ufności z wykorzystaniem jądrowej estymacji funkcji gęstości, [w:] Zbigniew E. Zieliński (red.), Rola informatyki w naukach ekonomicznych i społecznych. Innowacje i implikacje interdyscyplinarne, Wydawnictwo Wyższej Szkoły Handlowej w Kielcach, Kielce, 2, 100–110. | pl |
| dc.references | Koronacki Jacek, Ćwik Jan, (2005), Statystyczne systemy uczące się, Wydawnictwa Naukowo-Techniczne, Warszawa. | pl |
| dc.references | Kot Stanisław, (2008), Polaryzacja ekonomiczna. Teoria i zastosowanie, Polskie Wydawnictwo Naukowe, Warszawa. | pl |
| dc.references | Krzyśko Mirosław, Wołyński Waldemar, Górecki Tomasz, Skorzybut Michał, (2008), Systemy uczące się. Rozpoznawanie wzorców analiza skupień i redukcja wymiarowości, Wydawnictwa Naukowo-Techniczne, Warszawa. | pl |
| dc.references | Kulczycki Piotr, (2005), Estymatory jądrowe w analizie systemowej, Wydawnictwa Naukowo-Techniczne, Warszawa. | pl |
| dc.references | Kyung-Joon Cha, Schucany William R., (1998), Nonparametric Kernel Regression Estimation Near Endpoints, „Journal of Statistical Planning and Inference”, 66, 289–304. | pl |
| dc.references | Kvam Paul H., Vidakovic Brani, (2007), Nonparametric Statistics with Applications to Science and Engineering, Wiley Series in Probability and Statistics, Wiley-Interscience, John Wiley and Sons, Inc., Hoboken, New Jersey. | pl |
| dc.references | Li Qi, Racine Jeffrey Scott, (2007), Nonparametric Econometrics. Theory and Practice, Princeton University Press, Princeton and Oxford. | pl |
| dc.references | Loader Clive R., (1999), Bandwidth Selection: Classical or Plug-in, „The Annals of Statistics”, 27, 2, 415–438. | pl |
| dc.references | Lovric Miodrag, (1999), International Encyclopedia of Statistical Science, Springer-Verlag, Berlin, Heidelberg. | pl |
| dc.references | Mackenzie Mark, Tieu Kiet, (2004), Asymmetric Kernel Regression, http://ro.uow.edu.au/engpapers/ 29 [13.03.2016]. | pl |
| dc.references | Malec Peter, Schienle Melanie, (2013), Nonparametric Kernel Density Near the Boundary, „Computational Statistics and Data Analysis”, preprint, http://papers.ssrn.com/sol3/papers. cfm?abstract_id=2342165 [13.03.2015]. | pl |
| dc.references | Mammen Enno, (1994), On Qualitative Smoothness of Kernel Density Estimates, http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.2622 [13.08.2014]. | pl |
| dc.references | Marchant Carolina, Bertin Karine, Leiva Victor, Saulo Helton, (2013), Generalized Birnbaum-Saunders Kernel Density Estimators and an Analysis of Financial Data, „Computational Statistics and Data Analysis”, 63, 1–15. | pl |
| dc.references | Markovich Natalia, (2007), Nonparametric Analysis of Univariate Heavy-Tailed Data. Research and Practice, Wiley Series in Probability and Statistics, John Wiley and Sons, Ltd, The Atrium, Southern Gate, Chichester. | pl |
| dc.references | Marron J. Steve, (1993), Assessing Bandwidth Selectors with Visual Error Criteria, http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.7952 [13.08.2014]. | pl |
| dc.references | Marron J. Steve, Wand Matthew P., (1992), Exact Mean Integrated Squared Error, „The Annals of Statistics”, 20, 2, 712–736. | pl |
| dc.references | Müller Hans-Georg, (1984), Smooth Optimum Kernel Estimators of Densities, Regression Curves and Modes, „The Annals of Statistics”, 12, 2, 766–774. | pl |
| dc.references | Müller Hans-Georg, Petersen Alexander, (2016), Density Estimation Including Examples, anson.ucdavis.edu/~mueller/encycl5–1.pdf [17.05.2016]. | pl |
| dc.references | Noether Gottfried E., (1984), Nonparametrics: The Early Years – Impressions and Recollections, „The American Statistician”, 38, 3, 173–178. | pl |
| dc.references | Ostasiewicz Walenty, (2012), Myślenie statystyczne, Wolters Kluwer Polska Sp. z o.o., Warszawa. | pl |
| dc.references | Pagan Adrian, Ullah Aman, (1999), Nonparametric Econometrics, Cambridge University Press, Cambridge, Melbourne. | pl |
| dc.references | Park Byeong U., Marron J. Steve, (1990), Comparison of Data-Driven Bandwidth Selectors, „Journal of the American Statistical Association”, 85, 409, 66–72. | pl |
| dc.references | Parzen Emanuel, (1962), On Estimation of a Probability Density Function and Mode, „Annals of Mathematical Statistics”, 33, 3, 1065–1076. | pl |
| dc.references | Pearson Karl, (1895), Contributions to the Mathematical Theory of Evolution. II. Skew Variation in Homogeneous Material, „Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences”, 186, 343–414. | pl |
| dc.references | Pearson Karl, (1900), On the Criterion That a Given System of Deviations From the Probable in the Case of a Correlated System of Variables is Such That it Can be Reasonably Supposed to Have Arisen From Random Sampling, „Philosophical Magazine”, 5, 157–175. | pl |
| dc.references | Pearson Karl, (1911), On the Probability That Two Independent Distributions of Frequency are Really Samples from the Same Population, „Biometrika”, 8, 250–254. | pl |
| dc.references | Pomĕnková Jitka, (2008), Remarks on Optimum Kernels and Optimum Boundary Kernel, „Applications of Mathematics”, 53, 4, 305–317. | pl |
| dc.references | Raykar Vikas C., Duraiswami Ramani, Zhao Linda H., (2010), Fast Computation of Kernel Estimators, „Journal of Computational and Graphical Statistics”, 19, 1, 205–220. | pl |
| dc.references | Rosenblatt Murray, (1956), Remarks on Some Nonparametric Estimates of a Density Function, „Annals of Mathematical Statistics”, 27, 3, 832–837. | pl |
| dc.references | Ruzgas Tomas, Drulyrè Indrè, (2013), Kernel Density Estimation for Gaussian Mixture Models, „Lithuanian Journal of Statistics”, 52, 1, 14–21. | pl |
| dc.references | Rychlik Tomasz, (1995), A Class of Unbiased Kernel Estimates of a Probability Density Function, „Applicationes Mathematicae”, 22, 4, 485–497. | pl |
| dc.references | Sainudiin Raazesh, Lee Dominic, (2011), Computational Statistical Experiments in MATLAB, http://www.math.canterbury.ac.nz/~r.sainudiin/courses/STAT459/CSEBook.pdf [17.12.2015]. | pl |
| dc.references | Saulo Helton, (2013), Essays on Birnbaum-Saunders Models, www.lume.ufrgs.br/handle/10183/87375?locale=en [17.03.2015]. | pl |
| dc.references | Saulo Helton, Leiva Víctor, Ziegelmann Flavio A., Marchant Carolina, (2012), Density Estimation Using Skew-Birnbaum-Saunders Kernels, http://bibliotecadigital.fgv.br/ocs/index.php/sbe/EBE12/paper/view/3749 [17.03.2015]. | pl |
| dc.references | Saulo Helton, Leiva Víctor, Ziegelmann Flavio A., Marchant Carolina, (2013), A Nonparametric Method for Estimating Densities Based on Skewed Birnbaum-Saunders Distributions Applied to Environmental Data, „Stochastic Environmental Research and Risk Assessment”, 27, 1479–1491. | pl |
| dc.references | Scaillet Olivier, (2004), Density Estimation Using Inverse and Reciprocal Inverse Gaussian Kernels, „Journal of Nonparametric Statistics”, 16, 214–226. | pl |
| dc.references | Scheffè Henry, (1943), Statistical Inference in Non-parametric Case, „The Annals of Mathematical Statistics”, 32, 506–523. | pl |
| dc.references | Schuster Eugene F., (1969), Estimation of a Probability Density Function and its Derivatives, „The Annals of Mathematical Statistics”, 40, 4, 1187–1195. | pl |
| dc.references | Sclocco Tonino, Di Marzio Marco, (2001), A Note on Kernel Density Estimation for Non-Negative Random Variables, „Statistical Methods and Applications”, 10, 67–79. | pl |
| dc.references | Scott David W., (2015), Multivariate Density Estimation. Theory, Practice and Visualization, John Wiley and Sons, Inc., Hoboken, New Jersey. | pl |
| dc.references | Scott David W., Terrell George R., (1987), Biased and Unbiased Cross-Validation in Density Estimation, „Journal of the American Statistical Associations”, 82, 1131–1146. | pl |
| dc.references | Scott David W., Wand Matt P., (1991), Feasibility of Multivariate Density Estimates, „Biometrika”, 78, 1, 197–205. | pl |
| dc.references | Sheather Simon J., Jones M. Chris, (1991), A Reliable Data-based Bandwidth Selection Method for Kernel Density Estimation, „Journal of the Royal Statistical Society B”, 53, 3, 683–690. | pl |
| dc.references | Silverman Bernard W., (1986), Density Estimation for Statistics and Data Analysis, Chapman and Hall, London. | pl |
| dc.references | Stone Charles J., (1977), Consistent Nonparametric Regression, „The Annals of Statistics”, 5, 4, 595–645. | pl |
| dc.references | Stone Charles J., (1984), An Asymptotically Optimal Window Selection Rule for Kernel Density Estimates, „The Annals of Statistics”, 12, 1285–1297. | pl |
| dc.references | Stone Charles J., (1994), The Use of Polynomial Splines and Their Tensor Products in Multivariate Function Estimation, „The Annals of Statistics”, 22, 118–171. | pl |
| dc.references | Sturges Herbert A., (1926), The Choice of a Class Interval, „Journal of the American Statistical Association”, 21, 153, 65–66. | pl |
| dc.references | Śliwicki Dominik, (2012), Jądrowy test liniowości, „Acta Universitatis Nicolai Copernici”, Ekonomia XLIII, 2, 183–198. | pl |
| dc.references | Terrell George R., Scott David W., (1985), Oversmoothed Nonparametric Density Estimates, „Journal of the American Statistical Association”, 80, 389, 209–214. | pl |
| dc.references | Tooth Sarah M., Dobelman John A., (2016), A New Look at Generalized Means, „Applied Mathematics”, 7, 468–472. | pl |
| dc.references | Turlach Berwin A., (1992), Discretization Methods for Average Derivative Estimation, Discussion Paper 9232, C.O.R.E., http://staffhome.ecm.uwa.edu.au/~00043886/cv/rep.html [6.12.2013]. | pl |
| dc.references | Turlach Berwin A., (1993), Bandwidth Selection in Kernel Density Estimation: A Review, Discussion Paper 9317, Institut de Statistique, C.O.R.E., http://staffhome.ecm.uwa.edu.au/~00043886/cv/rep.html [6.12.2013]. | pl |
| dc.references | Van Ryzin John, Kim Bock K., (1980), On the Asymptotic Distribution of a Histogram Density Estimator, www.osti.gov/servlets/purl/5271176/ [14.12.2015]. | pl |
| dc.references | Wald Abraham, Wolfowitz Jacob, (1939), Confidence Limits for Continuous Distribution Functions, „The Annals of Mathematical Statistics”, 10, 2, 105–118. | pl |
| dc.references | Wand Matt P., Devroye Luc, (1993), How Easy is a Given Density to Estimate?, „Computational Statistics and Data Analysis”, 16, 311–323. | pl |
| dc.references | Wand Matt P., Jones M. Chris, (1995), Kernel Smoothing, Chapman and Hall, London. | pl |
| dc.references | Wand Matthew P., Schucany William R., (1990), Gaussian-based Kernels, „The Canadian Journal of Statistics”, 18, 3, 197–204. | pl |
| dc.references | Wilcoxon Frank, (1945), Individual Comparisons by Ranking Methods, „Biometrics Bulletin”, 1, 6, 80–83. | pl |
| dc.references | Wolfowitz Jacob, (1942), Additive Partition Functions and a Class of Statistical Hypotheses, „The Annals of Mathematical Statistics”, 13, 247–279. | pl |
| dc.references | Woodroofe Michael, (1970), On Choosing a Delta-Sequence, „The Annals of Mathematical Statistics”, 41, 5, 1665–1671. | pl |
| dc.references | Zambom Adriano Z., Dias Ronaldo, (2012), A Review of Kernel Density Estimation with Application to Econometrics, http://arxiv.org/pdf/1212.2812v1.pdf [28.02.2014]. | pl |
| dc.references | Zieliński Ryszard, (2004), Optimal Quantile Estimators Small Sample Approach, IMPAN, www.impan.pl/Preprints/p653.pdf [6.03.2014]. | pl |
| dc.references | Zinde-Walsh Victoria, (2005), Kernel Estimation when Density does not Exist, https://ideas.repec.org/p/mtl/montec/09-2005.html [28.02.2014]. | pl |
| dc.references | Zhang Shunpu, (2010), A Note on the Performance of the Gamma Kernel Estimators at the Boundary, „Statistics and Probability Letters”, 80, 548–557. | pl |
| dc.references | Zhang Shunpu, Karunamuni Rohana J., (2010), Boundary Performance of the Beta Kernel Estimators, „Journal of Nonparametric Statistics”, 22, 1, 81–104. | pl |
| dc.identifier.doi | 10.18778/8088-280-5 | |