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Showing 10 results for Chinipardaz
Mohammad Reza Alavi, Rahim Chinipardaz,
Volume 1, Issue 1 (9-2007)
Abstract
The classical analysis is based on random samples. However, in many situations the observations are recorded according to a nonnegative function of observations. In this case the mechanism of sampling is called weighted sampling. The usual statistical methods based on a weighted sample may be not valid and have to be adjusted. In this paper adjusted methods under some particular weight functions for normal distribution are studied and a new distribution called double normal distribution, is introduced as a weighted normal distribution.
Rahim Chinipardaz, Hoda Kamranfar,
Volume 3, Issue 1 (9-2009)
Abstract
This paper is concerned with the study of the effect of outliers in GARCH models. Four common outliers are considered: additive outliers, innovation outliers, level change and temporary change. Each of the outlier is embedded to a GARCH model and then the effectness of outliers in this model is studied. The residuals of the models have been investigated for both cases, the usual GARCH model and the GARCH model in the present of outliers.
Khadijeh Mehri, Rahim Chinipardaz,
Volume 5, Issue 2 (2-2012)
Abstract
This article is concerned with the comparison between posterior probability and p-value in two-parameter exponential distribution when the location parameter is considered as extra (nuisance) parameter. It has been shown that for a fixed p-value the posterior probability is increases as the number of observations gets large value. It means that it may be different results between classical and Bayesian point of view. This irreconcilability between classical evidence and Bayesian evidence is remained if we compare the lower bound of posterior probability under a class of reasonable prior distributions.
Sayed Mohammad Reza Alavi, Safura Alibabaie, Rahim Chinipardaz,
Volume 11, Issue 2 (3-2018)
Abstract
The standard Beta distribution is a suitable distribution for modeling the data that include proportions. In many situations which the data of proportions include a considerable number of zeros and ones, the inflated beta distributions are more appropriate. When probabilities of recording such observations are proportional to a nonnegative weight function, the recorded observations distributed as a weighted inflated Beta. This article focuses on the size biased inflated Beta distribution as a special case of weighted inflated Beta distribution with the power weight function. Some properties of this distribution is studied and its parameters are estimated using maximum likelihood and method of moments approaches. The estimators are compared via a simulation study. Finally, the real mortality data set is fitted for this model.
Reza Zabihi Moghadam, Rahim Chinipardaz, Gholamali Parham,
Volume 12, Issue 1 (9-2018)
Abstract
In this paper a method has been given to detect the shocks in structural time series using Kalman filter algorithm. As the Kalman filter algorithm is used for state space forms which include ARMA models as an especial case, the suggested method can be used for more general time series than linear models. Five shocks; additive outlier, level change, seasonal change, periodic change and slope change have been reviewed with this method. The performance of suggested method has been shown via a simulation study. The marriage data set from England has been considered as a real data set to study.
Behzad Mansouri, Rahim Chinipardaz,
Volume 12, Issue 2 (3-2019)
Abstract
In this paper, using Band matrix, a method has been proposed to estimating the covariance matrix of the ARMA model and the likelihood function of the ARMA model with diagonal covariance matrix has been obtained and approximations for Kullback-Leibler and Chernoff criteria were presented. In addition, two rules for discriminating the ARMA models has been proposed. A simulation and real data sets are used to illustrate the performance of the proposed rules. Significant reduction of the calculations for large time series and low discrimination error rate are two characteristics of the proposed rules. In addition no need to normal assumption is showed in a theorem.
Ghasem Rekabdar, Rahim Chinipardaz, Behzad Mansouri,
Volume 13, Issue 1 (9-2019)
Abstract
In this study, the multi-parameter exponential family of distribution has been used to approximate the distribution of indefinite quadratic forms in normal random vectors. Moments of quadratic forms can be obtained in any orders in terms of representation of the quadratic forms as weighted sum of non-central chi-square random variables. By Stein's identity in exponential family, we estimated parameters of probability density function. The method handled in some examples and we indicated this method suitable for approximating the quadratic form distribution.
Mohammad Reza Yeganegi, Rahim Chinipardaz,
Volume 13, Issue 1 (9-2019)
Abstract
This paper is investigating the mixture autoregressive model with constant mixing weights in state space form and generalization to ARMA mixture model. Using a sequential Monte Carlo method, the forecasting, filtering and smoothing distributions are approximated and parameters f the model is estimated via the EM algorithm. The results show the dimension of parameter vector in state space representation reduces. The results of the simulation study show that the proposed filtering algorithm has a steady state close to the real values of the state vector. Moreover, according to simulation results, the mean vectors of filtering and smoothing distribution converges to state vector quickly.
Sayed Mohammad Reza Alavi, Mohammad Joharzadeh, Rahim Chinipardaz,
Volume 13, Issue 1 (9-2019)
Abstract
Usually in survey sampling when the sensitive questions are asked directly, the respondents do not provide true answers. The randomized response techniques have been introduced to protect the privacy responses. In this article we focus on Simons randomized response technique for qualitative variables. Using the combination of the two different Simmons’ models, a new combined randomized response technique is introduced to increase protection of privacy. Using simulation in R package, efficiency of the proposed model is compared to the Simmons’ and Alavi and Tajodini's (1394) models. Finally, the proposed model has been employed for estimating the proportion of student cheating in Shahid Chamran University.
Zahra Nicknam, Rahim Chinipardaz,
Volume 19, Issue 1 (9-2025)
Abstract
Classical hypothesis tests for the parameters provide suitable tests when the hypotheses are not restricted. The best are the uniformly most powerful test and the uniformly most powerful unbiased test. These tests are designed for specific hypotheses, such as one-sided and two-sided for the parameter. However, in practice, we may encounter hypotheses that the parameters under test have typical restrictions in the null or alternative hypothesis. Such hypotheses are not included in the framework of classical hypothesis testing. Therefore, statisticians are looking for more powerful tests than the most powerful ones. In this article, the union-intersection test for the sign test of variances in several normal distributions is proposed and compared with the likelihood ratio test. Although the union-intersection test is more powerful, neither test is unbiased. Two rectangular and smoothed tests have been examined for a more powerful test.
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