Warianty tytułu
On Determining the Mode of a Continuous Variable in Raw Data
Języki publikacji
Abstrakty
Celem pracy jest przedstawienie różnych możliwości wyznaczania dominanty cechy ciągłej w szeregach szczegółowych. (...) Równoległym celem pracy jest porównanie efektywności metod szacowania dominanty dla rozkładów o różnym stopniu asymetrii. (fragment tekstu)
One of the main descriptive characteristics is the mode. For continuous variables it is not always easy to properly determine the mode. There are some estimates of the mode provided in literature, however, unlike the median or the arithmetic mean, for the mode there does not exist the estimator which would be commonly considered as the best one. Moreover, in many statistical textbooks and computer packages this problem seems to be ignored. In this paper authors consider seven different methods of estimation the mode presented in literature. The efficiency of the estimation procedures has been evaluated on the basis simulation experiments for the normal and lognormal distributions with different degrees of skewness. The evaluation criteria of those procedures involve not only the efficiency of estimation but also simplicity of computation, which is an important aspect of teaching statistics. (original abstract)
Rocznik
Strony
107--120
Opis fizyczny
Twórcy
Bibliografia
- Bickel D.R. (2002), Robust Estimators of the Mode and Skewness of Continuous Data, Computational Statistics & Data Analysis 39.
- Bickel D.R. (2003), Robust and Efficient Estimation of the Mode of Continuous Data: The Mode as a Viable Measure of Central Tendency, Journal of Statistical Computation and Simulation 73.
- Bickel D.R. (2006), On a Fast, Robust Estimator of the Mode, Computational Statistics & Data Analysis 12.
- Grenander U., (1965), Some Direct Estimates of the Mode, Annals of Mathematical Statistics" 36.
- Hall P. (1982), Limit Theorems for Estimators Based on Inverses of Spacings of Order Statistics, The Annals of Probability 10.
- Rousseeuw, P.J., Leroy A.M. (1987) Robust Regression and Outlier Detection, Wiley, New York.
- Sobczyk M. (2002), Statystyka, PWN Warszawa.
- Szulc B. (1976), Statystyka dla ekonomistów, PWE, Warszawa.
- Yule G.U., Kendall M.G. (1966), Wstęp do teorii statystyki, PWN, Warszawa.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171194219