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Full-Text Articles in Statistical Models
Generalized Weibull And Inverse Weibull Distributions With Applications, Valeriia Sherina
Generalized Weibull And Inverse Weibull Distributions With Applications, Valeriia Sherina
Electronic Theses and Dissertations
In this thesis, new classes of Weibull and inverse Weibull distributions including the generalized new modified Weibull (GNMW), gamma-generalized inverse Weibull (GGIW), the weighted proportional inverse Weibull (WPIW) and inverse new modified Weibull (INMW) distributions are introduced. The GNMW contains several sub-models including the new modified Weibull (NMW), generalized modified Weibull (GMW), modified Weibull (MW), Weibull (W) and exponential (E) distributions, just to mention a few. The class of WPIW distributions contains several models such as: length-biased, hazard and reverse hazard proportional inverse Weibull, proportional inverse Weibull, inverse Weibull, inverse exponential, inverse Rayleigh, and Frechet distributions as special cases. Included …
An Investigation Of Sensitivity Of An F Test In Locating Change Points In Linear Regression, Jing Sun
An Investigation Of Sensitivity Of An F Test In Locating Change Points In Linear Regression, Jing Sun
Electronic Theses and Dissertations
Change point is a statistic phenomenon, which has many direct applications in climatology, bioinformatics, finance, oceanography and medical imaging. In this thesis, we investigate the sensitivity of the F-test for detecting change points in linear regression, using a two-phase linear regression model. it offers an effective method to detect "undocumented" change points using a form of an F-test. Using simulated data, we explore its sensitivity and accuracy with respect t different parameters in the model.
Exponentially Weighted Moving Average Charts For Monitoring The Process Generalized Variance, Anna Khamitova
Exponentially Weighted Moving Average Charts For Monitoring The Process Generalized Variance, Anna Khamitova
Electronic Theses and Dissertations
The exponentially weighted moving average chart based on the sample generalized variance is studied under the independent multivariate normal model for the vector of quality measurements. The performance of the chart is based on an analysis of the chart's initial and steady-state run length distributions. The three methods that are commonly used to determinate run length distribution, simulation, the integral equation method, and the Markov chain approximation are discussed. The integral equation and Markov chain approaches are analytical methods that require a nu- merical method for determining the probability density and cumulative distribution functions describing the distribution of the sample …