Computational Statistics
Manijeh Mahmoodi; Mohammad Reza Salehi Rad; Farzad Eskandari
Abstract
AbstractThe novel corona virus (covid-19) spread quickly from person to another and one of the basic aspects of the country management has been to prevent the spread of this disease. So the prediction of its expansion is very important. In such matters, the estimation of new cases and deaths in covid-19 ...
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AbstractThe novel corona virus (covid-19) spread quickly from person to another and one of the basic aspects of the country management has been to prevent the spread of this disease. So the prediction of its expansion is very important. In such matters, the estimation of new cases and deaths in covid-19 has been considered by researchers. we propose an estimation of the statistical model for predicting the new cases and the new deaths by using the vector autoregressive (VAR) model with the multivariate skew normal (MSN) distribution for the asymmetric shocks and predict the samples data. The maximum likelihood (ML) method is applied to estimation of this model for the weekly data of the new cases and the new deaths of covid-19. Data are taken from World Health Organization (WHO) from March 2020 until March 2023 Iran country. The performance of the model is evaluated with the Akaike and the Bayesian information criterions and the mean absolute prediction error (MAPE) is interpreted.
Computational Statistics
Arezoo Asoodeh; Amir Hossein Ghatari; Ehsan Bahrami Samani
Abstract
We propose a novel parametric distribution, termed the Beta Modified Exponential Power Series (BMEPS) distribution, capable of modeling increasing, decreasing, bathtub-shaped, and unimodal failure rates. Constructed from addressing a latent complementary risk problem, this distribution arises from a ...
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We propose a novel parametric distribution, termed the Beta Modified Exponential Power Series (BMEPS) distribution, capable of modeling increasing, decreasing, bathtub-shaped, and unimodal failure rates. Constructed from addressing a latent complementary risk problem, this distribution arises from a combination of the Beta Modified Exponential (BME) and power series distributions. Within this new distribution, several important distributions discussed in the literature, such as the Beta Modified Exponential Poisson (BMEP), Beta Modified Exponential Geometric (BMEG), and Beta Modified Exponential Logarithmic (BMEL) distributions, exist as special submodels. This work provides a comprehensive mathematical treatment of the new distribution, offering closed-form expressions for its density, cumulative distribution, survival function, failure rate function, the r-th raw moment, and moments of order statistics. Furthermore, we delve into maximum likelihood estimation and present formulas for the elements comprising the Fisher information matrix. Finally, to showcase the flexibility and potential applicability of the new distribution, we apply it to a real dataset.
Computational Statistics
Reza Pourtaheri
Abstract
Traditionally, the statistical quality control techniques utilize either an attributes or variables product quality measure. Recently, some methods such as three-level control chart have been developed for monitoring multi attribute processes. Control chart usually has three design parameters: the sample ...
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Traditionally, the statistical quality control techniques utilize either an attributes or variables product quality measure. Recently, some methods such as three-level control chart have been developed for monitoring multi attribute processes. Control chart usually has three design parameters: the sample size (n), the sampling interval (h) and the control limit coefficient (k).The design parameters of the control chart are generally specified according to statistical or/and economic criteria. The variable sampling interval (VSI) control scheme has been shown to provide an increase to the detecting efficiency of the control chart with fixed sampling rate (FRS). In this paper a method is proposed to conduct the economic-statistical design for variable sampling interval of the three-level control charts. We use the cost model developed by Costa and Rahim and optimize this model by genetic algorithm approach. We compare the expected cost per unit time of the VSI and FRS 3-level control charts. Results indicate that the proposed chart has improved performance.
