ISSN: 1680-855X

Volume 5, Issue 8

Volume 5, Issue 8, Autumn 2005, Page 1-196


COMBINED NON-QUADRATIC MODELS AS A BASIS FOR CG-A LGORITHMS

Abbas Y. AL-Bayati; Abbas H. Taqi

IRAQI JOURNAL OF STATISTICAL SCIENCES, Volume 5, Issue 8, Pages 1-14

In this paper,a new extended (CG) algorithms is proposed. It is in fact, a particular type of the Conjugate Gradient (CG) method which employs non-quadratic rational model, and based on inexact line searches. The Flecther and Reeves restarting criterion was employed to the standard and New versions and gave dramatic savings in computational time. The new algorithms is were promising in general, seven non linear tests function with different versions were used.

Comparison Between Ordinary Method and Robust Method to estimate the Parameters of the Bivariate Mixed Model, ARMA(1,1)

IRAQI JOURNAL OF STATISTICAL SCIENCES, Volume 5, Issue 8, Pages 1-19

A condensed study was done to compare between the ordinary estimators. In particular the maximum likelihood estimator and the robust estimator, to estimate the parameters of the bivariate mixed model of order one, namely BARMA(1,1).
Simulation experiments were done for varieties of BARMA(1,1), using small, moderate and large sample sizes, where some new results were obtained. MAPE was used as a statistical criterion for comparison.

HIGH RESOLUTION IMAGE CLASSIFICATION

Wasfi Taher Saalih

IRAQI JOURNAL OF STATISTICAL SCIENCES, Volume 5, Issue 8, Pages 15-21

Classification is an important field with many applications. In particular, the classification of digital imagery has important applications in the mapping community. In this paper the comparison of three different classification methods on LANDSAT imagery of Erbil City - IRAQ: neural networks, nearest-neighbor, and discriminant analysis are made.
Out of the three approaches, k-nearest neighbors performed the best; next in accuracy was neural networks, and then discriminant analysis.

Studying Consistency of Some Flitters Using Simulation

IRAQI JOURNAL OF STATISTICAL SCIENCES, Volume 5, Issue 8, Pages 20-39

ABSTRACT
This paper includes a simulation study of three well-known filters in real lift application. These filters are - filter, Kalman filter and FIR filter. Noisily realizations were generated from three stochastic models and depending on three different families of probability distribution of noise. The modern computer application MATLAB 6 is used . The simulation results indicated that FIR filter is more powerful than the other two filters.

Comparison of Spline Methods for estimating Nonparametric Regression Curve

IRAQI JOURNAL OF STATISTICAL SCIENCES, Volume 5, Issue 8, Pages 40-62

This research is focusing on methods related to smoothing Nonparametric Regression Functions. This is for the purpose of producing the best methods convenient for various methods. Thus, the most important purpose of the research is to find what the studies so far have offered in the field of Nonparametric Regression. Also to find alternative or modified methods, which are reliable for the treatment of failure regarding the methods in use, for example for the treatment of failure for penalized shrinkage method which depends on truncated Polynomial Regression spline model, especially for special models ,we suggest modification of knots make method more efficiency.
A simulation model has been performed with different distributions, for a number of methods. To verify the performance of such methods, many criteria have been carried out.

The Use of Neural Networks in Forecasting of Time Series with Application on Consumption of Electrical Power in Mosul City

IRAQI JOURNAL OF STATISTICAL SCIENCES, Volume 5, Issue 8, Pages 63-79

Forecasting of future behavior of time series is one of the important subjects in statistical sciences, because of its important need in different areas of life. Interest in forecasting had increased in the recent years, and some new techniques in the field of computer science, like Artificial Neural Networks (ANN), had appeared. These techniques have the ability learning and self- adaptation with any model, and don’t need assumptions on the nature of time series. On the other hand the classical forecasting methods, like Box-Jenkins method, need hard conditions. Hence, the need for a comparison between classical methods in forecasting of time series with ANN technique arose.

Application of a Markov chain Model on the popular transformation between the cities of (Nineva, Saladean, Tameem) for the period 1977-1997

IRAQI JOURNAL OF STATISTICAL SCIENCES, Volume 5, Issue 8, Pages 80-95

In this paper we study the migration of population among the three Iraqi cities: Nineva , Saladean, Tameem by considering these this migrations as a Markov chain with three states which represent the transitions among these cities .We obtain a transition matrix (3x3) to represent these states and we obtain that this chain is Ergodic and we find the mean and the variance of the waiting time ,the time between consecutive transition and the duration of an excursion at each state.

Some Identification Methods of Mixed Model ARMA(1,1) and its Probabilistics Properties when Detetcting Random Error belong to Poisson Distribution

IRAQI JOURNAL OF STATISTICAL SCIENCES, Volume 5, Issue 8, Pages 120-139

Most of the time series that appear in many economical geophysical and otherphenomenas are driven by non-Gaussian random error (at), so the aim of this paper is to investigate some of the probabilistic properties of Gaussian and non-Gaussian mixed model ARMA(1,1), and the identification methods of this model.
The researchers have theoretically derived the characteristic function the first four moments and the skeweness and Kurtosis coeficients for (at) for Gaussian distribution and non-Gaussian distribution (poisson) and simulation experiment were used to confirm the accuracy of the theoretical results, We have also declared the identification sample autocorrelation function (ESACF) and (Kumar) method (c-table) depending upon the pade approximation and we have suggested a method depending upon the extended sample partial autocorrelation function (ESPACF) to ascertain the efficiency of suggested method.

Building Parsimonious Dynamic System for Time Series

IRAQI JOURNAL OF STATISTICAL SCIENCES, Volume 5, Issue 8, Pages 140-165

In this paper the radial basis function method is used for the generation of models of time series. It has been arrived at a model for nonlinear time series. It has also been found that the error is restricted between zero and one. The probability characteristics have been explained for such series accompanied by a complete analysis for the residuals of model. A simulation has been done for the purpose of examination the generative information of the model. which have the same information characteristics.

Bayesian Estimation of Parameter of Spatial Quadratic Decay Model

IRAQI JOURNAL OF STATISTICAL SCIENCES, Volume 5, Issue 8, Pages 181-196

This paper deals with the problem of estimating parameters of spatial quadratic model by Bayesian technique. This technique involves the prior information of the first and second moment of the parameters. This estimation model is called the Bayesian quadratic unbiased estimator, which is linear in the parameters. The results of estimation are compared with the estimates of minimum norm quadratic unbiased estimators and the results are encouraging.
All algorithms of computation are written by using MatLAB programming.