1
1735-1294
Statistical Research and Training Center - Statistical Centre of Iran
82
General
Evaluation of Tests for Separability and Symmetry of Spatio-temporal Covariance Function
Behshad
Elham
Mohammadzadeh
Mohsen
1
9
2011
8
1
1
27
02
01
2016
02
01
2016
In recent years, some investigations have been carried out to examine the assumptions like stationarity, symmetry and separability of spatio-temporal covariance function which would considerably simplify fitting a valid covariance model to the data by parametric and nonparametric methods. In this article, assuming a Gaussian random field, we consider the likelihood ratio separability test, a variety of nonparametric and spectral tests of symmetry and also separability of spatio-temporal covariance function. Comparing the tests of symmetry and separability in a level of scenarios, the best ones would be introduced.
78
General
A Note on the Bivariate Maximum Entropy Modeling
Ashrafi
S.
Asadi
M.
1
9
2011
8
1
29
48
30
12
2015
30
12
2015
Let X=(X1 ,X2 ) be a continuous random vector. Under the assumption that the marginal distributions of X1 and X2 are given, we develop models for vector X when there is partial information about the dependence structure between X1 and X2. The models which are obtained based on well-known Principle of Maximum Entropy are called the maximum entropy (ME) models. Our results lead to characterization of some well-known bivariate distributions such as Generalized Gumbel, Farlie-Gumbel-Morgenstern and Clayton bivariate distributions. The relationship between ME models and some well known dependence notions are studied. Conditions under which the mixture of bivariate distributions are ME models are also investigated.
83
General
On Performance of Reconstructed Middle Order Statistics in Exponential Distribution
Razmkhah
M.
Khatib
B.
Ahmadi
J.
1
9
2011
8
1
49
62
02
01
2016
02
01
2016
In a number of life-testing experiments, there exist situations where the monitoring breaks down for a temporary period of time. In such cases, some parts of the ordered observations, for example the middle ones, are censored and the only outcomes available for analysis consist of the lower and upper order statistics. Therefore, the experimenter may not gain the complete information on failure times for all experimental units. So, the accuracy of some statistical inferences may be decreases. In this paper, the effect of reconstructing missing order statistics on the performance of the maximum likelihood estimator (MLE) of the mean of the exponential distribution is investigated. To illustrate the proposed procedure in the paper, a real example is presented and using a simulation study, it will be shown that the reconstructing missing order statistics improves the estimation of the parameter of interest.
84
General
Instability of the Determinants of Birth Intervals in Ahvaz-Iran: A Structural Change Modelling Approach
Rasekh
Abdolrahman
Imami
Hadi
1
9
2011
8
1
63
84
02
01
2016
02
01
2016
Birth interval is one of the major determinants of the fertility rate. In this paper structural change approach is used to study the instabilities in the effects of different socio-economic factors on birth intervals of children with respect to couplechr('39')s years of marriage factor in Ahvaz-Iran. A class of M-fluctuation tests for parameter instability is used and based on these tests different evidences of instability including the years of change and factors which changed are estimated and identified. The data analysed come from a sample of women referred to "Health and Medical Centreschr('39')chr('39') during October and November 2002.
79
General
M-estimators as GMM for Stable Laws Discretizations
Farbod
Davood
1
9
2011
8
1
85
96
30
12
2015
30
12
2015
This paper is devoted to "Some Discrete Distributions Generated by Standard Stable Densities" (in short, Discrete Stable Densities). The large-sample properties of M-estimators as obtained by the "Generalized Method of Moments" (GMM) are discussed for such distributions. Some corollaries are proposed. Moreover, using the respective results we demonstrate the large-sample properties for a parametric function.
85
General
Relative Entropy Rate between a Markov Chain and Its Corresponding Hidden Markov Chain
Yari
H.
Nikooravesh
Z.
1
9
2011
8
1
97
110
02
01
2016
02
01
2016
In this paper we study the relative entropy rate between a homogeneous Markov chain and a hidden Markov chain defined by observing the output of a discrete stochastic channel whose input is the finite state space homogeneous stationary Markov chain. For this purpose, we obtain the relative entropy between two finite subsequences of above mentioned chains with the help of the definition of relative entropy between two random variables then we define the relative entropy rate between these stochastic processes and study the convergence of it.
81
General
Estimation of Climate Zone Effects on Iranian Temperature, Humidity, and Precipitation using Functional Analysis of Covariance
Hosseini-nasab
E.
Kheirollahzadeh
N.
1
9
2011
8
1
111
133
30
12
2015
30
12
2015
Functional Data Analysis (FDA) has recently made considerable progress because of easier access to the data that are essentially in the form of curves. Although functional modeling of Iranian precipitation based on temperature or humidity was done before, here we use functional analysis of variance and covariance to analyze the weather data collected randomly from Iranian weather stations in 2010. Using a functional linear model in which the covariate (climate zones) and response variable (temperature or humidity) are functions, we estimate the coefficients via functional analysis of variance. As a result, we can determine how much of temperature or humidity variation in the weather stations is affected by the geographic areas. Using a functional analysis of covariance, we can also investigate that how much of the precipitation variation, can be expressed by the temperature residual effects or humidity residual effects (temperature or humidity effects after eliminating the climate impacts) and the corresponding climate effects.