Statistical Research and Training Center - Statistical Centre of Iran
Journal of Statistical Research of Iran JSRI
1735-1294
5
2
2009
3
1
Higher Order Moments and Recurrence Relations of Order Statistics from the Exponentiated Gamma Distribution
145
160
EN
I.
Shawky and
R.
Bakoban
rbakoban@yahoo.com
10.18869/acadpub.jsri.5.2.145
Order statistics arising from exponentiated gamma (EG) distribution are considered. Closed from expressions for the single and double moments of order statistics are derived. Measures of skewness and kurtosis of the probability density function of the rth order statistic for different choices of r, n and /theta are presented. Recurrence relations between single and double moments of rth order statistics are obtained. Single moment generating function (MGF) is derived in closed form. Also, we establish several recurrence relations between single MGF.
Order statistics, recurrence relations, single moments, double moments, moment generating function, exponentiated gamma distribution
http://jsri.srtc.ac.ir/article-1-116-en.html
http://jsri.srtc.ac.ir/article-1-116-en.pdf
Statistical Research and Training Center - Statistical Centre of Iran
Journal of Statistical Research of Iran JSRI
1735-1294
5
2
2009
3
1
On Some Properties and Estimation of a Skew Symmetric Density Function
161
170
EN
M.
Towhidi
mtowhidi@susc.ac.ir
M.
Shaghaghian
shaghaghian.m@gmail.com
10.18869/acadpub.jsri.5.2.161
In this paper we consider a general setting of skew-symmetric distribution which was constructed by Azzalini (1985), and its properties are presented. A suitable empirical estimator for a skew-symmetric distribution is proposed. In data analysis, by comparing this empirical model with the estimated skew-normal distribution, we show that the proposed empirical model has a better fit in density estimation, via some simulations.
Skew-distribution, skew-normal, skewness, kernel estimation
http://jsri.srtc.ac.ir/article-1-121-en.html
http://jsri.srtc.ac.ir/article-1-121-en.pdf
Statistical Research and Training Center - Statistical Centre of Iran
Journal of Statistical Research of Iran JSRI
1735-1294
5
2
2009
3
1
The Rate of Rényi Entropy for Irreducible Markov Chains
171
180
EN
Einollah
Pasha
pasha@saba.tmu.ac.ir
Leila
Golshani
leila_golshani@yahoo.com
hossein
Yari
yari@iust.ac.ir
10.18869/acadpub.jsri.5.2.171
In this paper, we obtain the Rényi entropy rate for irreducible-aperiodic Markov chains with countable state space, using the theory of countable nonnegative matrices. We also obtain the bound for the rate of Rényi entropy of an irreducible Markov chain. Finally, we show that the bound for the Rényi entropy rate is the Shannon entropy rate.
Rényi entropy rate, Shannon entropy rate, Rényi entropy, countable nonnegative matrices
http://jsri.srtc.ac.ir/article-1-117-en.html
http://jsri.srtc.ac.ir/article-1-117-en.pdf
Statistical Research and Training Center - Statistical Centre of Iran
Journal of Statistical Research of Iran JSRI
1735-1294
5
2
2009
3
1
Fitting Propagation Models with Random Grains, Method and Some Simulation Studies
181
192
EN
M.
Khazaei
m_ Khazaei@sbu.ac.ir
K.
Shafie
khalil.shafie@unco.edu
M.
Ganjali
m-ganjali@sbu.ac.ir
10.18869/acadpub.jsri.5.2.181
In this paper the regression problem for random sets of the Boolean model type is developed, where the corresponding poisson process of the model is related to some explanatory variables and the random grains are not affected by these variables. A model we call propagation model, is presented and some methods for fitting this model are introduced. Propagation model is applied in a simulation study
Random closed set, hitting functional, Boolean model, propagation model, generalized linear model
http://jsri.srtc.ac.ir/article-1-118-en.html
http://jsri.srtc.ac.ir/article-1-118-en.pdf
Statistical Research and Training Center - Statistical Centre of Iran
Journal of Statistical Research of Iran JSRI
1735-1294
5
2
2009
3
1
Effect of Non-Normality on Sampling Plan Using Yule’s Model
193
206
EN
R.
Singh
Mujahida
Sayyed
mujahida.sayyed@rediffmail.com
10.18869/acadpub.jsri.5.2.193
In this paper, the effect of non-normality on sampling plan using Yule’s model (second order auto regressive model {AR (2)}) represented by the Edgeworth series is studied for known $sigma$. The effect of using the normal theory sampling plan in a non-normal situation using Yule’s model is studied by obtaining the distorted errors of the first and second kind. As one will be interested in having a suitable sampling plan under Yule’s model for non-normal variables the values of n and k are determined.
Sampling plan, autoregressive process, edgeworth series, autocorrelation
http://jsri.srtc.ac.ir/article-1-120-en.html
http://jsri.srtc.ac.ir/article-1-120-en.pdf
Statistical Research and Training Center - Statistical Centre of Iran
Journal of Statistical Research of Iran JSRI
1735-1294
5
2
2009
3
1
Central Limit Theorem in Multitype Branching Random Walk
207
220
EN
A.
Rahimzadeh Sani
rahimsan@saba.tmu.ac.ir
10.18869/acadpub.jsri.5.2.207
A discrete time multitype (p-type) branching random walk on the real line R is considered. The positions of the j-type individuals in the n-th generation form a point process. The asymptotic behavior of these point processes, when the generation size tends to infinity, is studied. The central limit theorem is proved.
Central limit theorem, counting measure, intensity measure, multitype branching random walk
http://jsri.srtc.ac.ir/article-1-119-en.html
http://jsri.srtc.ac.ir/article-1-119-en.pdf
Statistical Research and Training Center - Statistical Centre of Iran
Journal of Statistical Research of Iran JSRI
1735-1294
5
2
2009
3
1
Point and Interval Estimation for the Burr Type III Distribution
221
233
EN
A.
Asgharzade
a.asgharzade@umz.ac.ir
M.
Abdi
me.abdi.z@gmail.com
10.18869/acadpub.jsri.5.2.221
In this paper, we study the estimation problems for the Burr type III distribution based on a complete sample. The maximum likelihood method is used to derive the point estimators of the parameter. An exact confidence interval and an exact joint confidence region for the parameters are constructed. Two numerical examples with real data set and simulated data, are presented to illustrate the methods proposed here.
Burr type III distribution, confidence interval, joint confidence region, maximum likelihood estimation
http://jsri.srtc.ac.ir/article-1-115-en.html
http://jsri.srtc.ac.ir/article-1-115-en.pdf