Displaying similar documents to “Robust estimation based on spacings in weighted exponential models”

Robust estimation of the scale and weighted distributions

Paweł Błażej (2007)

Applicationes Mathematicae

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The concept of robustness given by Zieliński (1977) is considered in cases where violations of models are generated by weight functions. Uniformly most bias-robust estimates of the scale parameter, based on order statistics, are obtained for some statistical models. Extensions of results of Zieliński (1983) and Bartoszewicz (1986) are given.

Exponential smoothing and resampling techniques in time series prediction

Maria Manuela Neves, Clara Cordeiro (2010)

Discussiones Mathematicae Probability and Statistics

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Time series analysis deals with records that are collected over time. The objectives of time series analysis depend on the applications, but one of the main goals is to predict future values of the series. These values depend, usually in a stochastic manner, on the observations available at present. Such dependence has to be considered when predicting the future from its past, taking into account trend, seasonality and other features of the data. Some of the most successful forecasting...

A weighted version of Gamma distribution

Kanchan Jain, Neetu Singla, Rameshwar D. Gupta (2014)

Discussiones Mathematicae Probability and Statistics

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Weighted Gamma (WG), a weighted version of Gamma distribution, is introduced. The hazard function is increasing or upside-down bathtub depending upon the values of the parameters. This distribution can be obtained as a hidden upper truncation model. The expressions for the moment generating function and the moments are given. The non-linear equations for finding maximum likelihood estimators (MLEs) of parameters are provided and MLEs have been computed through simulations and also for...

Time series analysis: recursive methods and their modifications for time series with outliers and missing observations.

Tomás Cipra, Asunción Rubio, José Trujillo (1991)

Extracta Mathematicae

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The recursive methods are popular in time series analysis since they are computationally efficient and flexible enough to treat various changes in character of data. This paper gives a survey of the most important type of these methods including their classification and relationships existing among them. Special attention is devoted to i) robustification of some recursive methods, capable of facing outliers in time series, and ii) modifications of recursive methods for time series with...

Improved inference for the generalized Pareto distribution under linear, power and exponential normalization

Osama Mohareb Khaled, Haroon Mohamed Barakat, Nourhan Khalil Rakha (2022)

Kybernetika

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We discuss three estimation methods: the method of moments, probability weighted moments, and L-moments for the scale parameter and the extreme value index in the generalized Pareto distribution under linear normalization. Moreover, we adapt these methods to use for the generalized Pareto distribution under power and exponential normalizations. A simulation study is conducted to compare the three methods on the three models and determine which is the best, which turned out to be the...

Finite mixture models with fixed weights applied to growth data

Marek Molas, Emmanuel Lesaffre (2012)

Biometrical Letters

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To model cross-sectional growth data the LMS method is widely applied. In this method the distribution is summarized by three parameters: the Box-Cox power that converts outcome to normality (L); the median (M); and the coeficient of variation (S). Here, we propose an alternative approach based on fitting finite mixture models with several components which may perform better than the LMS method in case the data show an unusual distribution. Further, we explore fixing the weights of the...