The Study of the Simulation of the Efficiency of Wavelet Estimation of Trend Functions under Long-term Dependence Errors
Narges
Hosseinioun
Assistant Professor, Department of Statistics, PayameNoor University
author
Najmeh
Alamshahi
Department of Statistics, PayameNoor University
author
text
article
2017
per
In this paper, we examine the estimation for trend functions in a time series model with Gaussian dependent residues with the aid of wavelet techniques. Using the simulations on the five different test functions and the process and taking into account the desired function, the factors affecting the error in our estimation have been discussed. The results show that the error rate of the wavelet method depends on the long-term dependence length. Finally, according to our simulations, the wavelet estimator method is compared with the so called classical methods of Kernel estimation and the results revealed that Wavelet estimations are more efficient.
دوفصلنامه گستره علوم آماری
دانشگاه پیام نور
2476-3632
2
v.
2 (بهار و تابستان 1396)
no.
2017
9
22
https://stat.journals.pnu.ac.ir/article_4714_677225a2a25a6b01a941fc500ef652af.pdf
The Nutrition Value Assessment and Replacement of Iranian Fruit and Vegetables Based on the Principal Component Analysis and Cluster Analysis
masomeh
hosseinpour
دانشجوی پیام نور
author
Alireza
Fakharzadeh Jahromi
Professor, Mathematics, Shiraz University of Technology & Fars Elite Foundation
author
text
article
2017
per
Despite the physicians and nutritionists recommendations to consume the fruits and vegetables, they point much less on how to choose fruits and vegetables in daily meals. In this study, with a novel approach, fruits and vegetables have been classified on the basis of their similar characteristics and the amount of certain nutrients. One of the goals of diet is the diversity and balance of nutrition; therefore the classification of fruits and vegetables on the basis of their nutritional value makes balancing the nutritional intake of these important food groups and also finding a suitable replacement for them feasible. In order to meet the nutritional needs, using principal component analysis and cluster analysis, fruits and vegetables are classified into several groups. MATLAB software was used for doing this classification.
دوفصلنامه گستره علوم آماری
دانشگاه پیام نور
2476-3632
2
v.
2 (بهار و تابستان 1396)
no.
2017
23
32
https://stat.journals.pnu.ac.ir/article_4715_26ab404126bca39603d94f1cea58d8ba.pdf
E-Bayesian and Hierarchical Bayesian estimators for the scale parameter of the Weibull distribution based on the Progressive Type II censoring with Three Loss Functions
Shahram
Yaghoobzadeh Shahrestani
Lecturer- Payame Noor University
author
text
article
2017
per
In this paper, the estimation of the scale parameter of a two-parameter Weibull distribution based on the Progressive Type II censoring samples has been considered. The E-Bayesian and Hierarchical Bayesian estimators for the scale parameter of the Weibull distribution based on the symmetric and asymmetric loss functions, such as the squared error (SE), general entropy (GE) and Linear exponential (LINEX) loss functions, are provided. Then, with the use of mean square error and absolute bias and through Monte Carlo simulation study, these methods are compared with each other and with E-Bayesian estimator.
دوفصلنامه گستره علوم آماری
دانشگاه پیام نور
2476-3632
2
v.
2 (بهار و تابستان 1396)
no.
2017
33
40
https://stat.journals.pnu.ac.ir/article_4716_9524e25ceb18c7c8a4d5bcee369f1010.pdf
INTRODUCING A NEW ESTIMATOR FOR ESTIMATING THE POPULATION MEAN IN THE PRESENCE OF MEASUREMENT ERRORS
Leader
Navaei
Assistant Professor
author
text
article
2017
per
In this paper we study the problem of estimation of population mean in the presence of measurement error simultaneously using information on a single auxiliary variable. We have developed a new estimator of population mean and compared it with some existing estimators under the situations when measurement errors occur simultaneously. The proposed estimators are theoretically compared with existing estimators. Empirical and simulation study is also conducted to assess the performance of proposed estimator.
دوفصلنامه گستره علوم آماری
دانشگاه پیام نور
2476-3632
2
v.
2 (بهار و تابستان 1396)
no.
2017
41
50
https://stat.journals.pnu.ac.ir/article_4717_1667fd6c70078a62fad4d840cf52fcd7.pdf
An alternative proof of de Bruijn’s identity for additive Gaussian noise channels with independent component
Abbas
Pak
Assistant Professor, Department of Statistics, Shahrekord University
author
IMAN
MAKHDOOM
Assistant Professor , Payame Noor University
author
text
article
2017
per
Additive noise channels are the most commonly used channels in signal processing. In these channels the received signal, random variable Y, is composed of a transmitted signal, random variable X, and an additive noise, random variable Z. One of the important problems studied on the received signal is the entropy of random variable Y. When additive noise Z is an independent Gaussian random variable with zero mean and unit variance, the elegant algebraic connection between differential entropy of output signal Y and Fisher information is stated through a relation known as the De Bruijn’s identity. In this paper, we first obtain a general relation for differentials of conditional distribution of output signal and use it to prove the relationship between the first derivative of differential entropy of output signal and its Fisher information. This method can be used for extending De Bruijn’s identity when the additive noise is distributed as another useful statistical distributions.
دوفصلنامه گستره علوم آماری
دانشگاه پیام نور
2476-3632
2
v.
2 (بهار و تابستان 1396)
no.
2017
51
56
https://stat.journals.pnu.ac.ir/article_4718_c939d06e6a942e2f6a5fc576d5da406f.pdf
Wavelet- Threshold Nonparametric Density Estimator and Covariance Structure of Wavelet Coefficients
Mahmoud
Afshari
Associate Professor, Department of Statistics, Persian Gulf University, Bushehr
author
Narges
Abbasi
Associate Professor, Department of Statistics, Payam Noor University
author
Alireza
Mehrdoost
M.Sc., Department of Statistics, Payam Noor University
author
text
article
2017
per
Wavelets are one of the newest achievements of mathematical science, which have many applications in other sciences especially statistics. In this paper, after introducing wavelet transforms, the nonparametric estimator of the density function is expressed by the nuclear wavelet and threshold wavelet method. Also variance-covariance of wavelet coefficient are investigated. At the end we survey the theoretical outcomes with numerical computation by using R software to compare purpose estimators.
دوفصلنامه گستره علوم آماری
دانشگاه پیام نور
2476-3632
2
v.
2 (بهار و تابستان 1396)
no.
2017
57
67
https://stat.journals.pnu.ac.ir/article_4719_f6e1bae9d460a09f70bead1982602ede.pdf