IRAOI JOURNAL OF STATISTICAL SCIENCES

he past few years have witnessed great progress in scientific
techniques. In addition , computer and information application
have been extended to include all scientific and human fields . In
this research , the mathematical model , Known as the Markovian
Model , has been used for modeling the eternal Laa Ilaah Illa
Allaah (There is no God but Allaah) after making use of the
computer for forming the transition matrix and processing it Fourthermore , some of the mathematical aspects related to this
relation statement have been studied in addition to the linguistic
investigation . The equilibrium distribution of the elements of the
statement has been worked out yielding a number of features of
numerical mircle.
The original scientific contribution that the in Allah has enabled
the researcher to arrive at an other evidence that the Glorious
Quraan is the eternal miracle over all ages and times

Forecasting is considered as one of the essential goals
regarding time series analysis, and forecasting accuracy
decreases the risk possibility regarding decision making. Whereat
the best model to represent the time series data, might not be the
same model used for forecasting. The forecasting evaluation
criterion used such as RMSE, MAPE, and MAE provides almost
different results concerning one time series, which confuse the
researcher to select the best model for forecasting. Therefore this
research deals with the problems of criterion differences results,
that affects the evaluation performance to select the best model,
and providing a statistical manner that employs the forecasting
criterion results that are mentioned as a weighted mean for each
model of ARIMA which is considered as a candidate model with
the least weighted mean that provides the best forecasting
performance. This has been applied on the monthly time series
for the water of the Tigris River (M-cu-m) that enters Mosul
City for the period 1963-1995. Meanwhile Box-Jenkins model
shows SARIMA (1,1,2) * (3,1,1) 12Very encouraging forecasting
results depending on the suggested manner compared with the
rest of models, meanwhile the best model for representing the
data is SARIMA (1,1,2) * (0,1,1) 12

This research analyze the cross relationship between world
prices for each of the Opec Oil, Euro exchange and Gold,in a system
of three equations by using Vector Autoregressive Model.To specify
and measure the direction of the causal relationship between the
variables. We use Granger causality and specify two equations
according to the last test,the first is:the relationship of the Euro
exchange with the Opec Oil prices,world Gold prices and with their
lags. The second is:the relationship of the Gold price with Euro
exchange,Opec Oil price with their lags.We use co-integration test
to determine if there is a long run relationship between the variables
in this research. For the purpose of analysis we use daily data for the
period from 2-1-2007 to 15-5-2008.It is obvious from the analysis
that there is interlocation relationship between world prices of the
variables in this study. It is also clear that is the variable of Opec
Basket price is Exogenous, while the world prices of each Gold and
Euro is Endogenous variables.

An experimental evaluation of an automatic algorithm for
segmentation of speech into Arabic syllabic units is reported
here. The parameter used for segmentation is the energy and
statistical parameter of acoustic signal and depending on the
characteristics of the phonology in Arabic language and the fairly
close correspondence between the acoustics and phonetics of
these syllables. Speech data of four speakers(2 males, 2 females),
consisting of mono-syllabic and poly-syllabic words were used to
test the segmentation algorithm. It is shown that the final output
result of this test is valid for a bout 85%

In this paper,we build two basic models to forecast a flow
water of the Tigris river which enters to mosul city . The first
model is Unobserved Components Model which is abbreviated
as UCM ,the second is Autoregressive and Moving Average
model which is mentioned as ARMA,we built 10 primary models
from ARMA to data of the time series of flow Tigris river after
we transfer the data to a standrized form to remove seasonal
effects . The best model which represented the data among
ARMA models which are mentionted above is ARMA(2,2) by
depending on the correction of Akaike information criterion
which is symbolized by AICc.while ARMA(1,2) model is the
best model for forecasting because it has a minimum mean
absolute error which is symbolized by MAE.We obtained that the
forecasting of flow water by UCM model is better than the
results of ARMA(1,2) model by depending on the criterion
MAE .

In this paper, we are concerned with the probability distribution
of random ridge factor. The estimator of regression parameter is
described as the shrunken estimator. Also we found the probability
density function of the shrinkage factor which belongs to familiar
probability density functions

In this reseach Monte Carlo simulation is used to calculate the
area of any circle as well as the volume of any sphere numerically.
Different functions are considered to test the performance of this
method, in addition to some improvement to give more satisfactory
results.

This research demonstrates a new scheduling algorithm for
multiprocessor in computer system, the problem of scheduling
were dealt in the case of (n) jobs which are represented by graph,
and the aim is to apply it on (m) independent processor, each job
requires (τ) running time. This study finds out a new algorithm
for scheduling a set of job for an arbitrary number of identical
processors. This algorithm was compared with scheduling
algorithm (CP/MISF) by using simulation and showed high
efficiency and easy to use.

Two machines failure time data and two simulated
examples have been studied through their reliability function and
failure rate using the exponentiated exponential distribution. It
could be considered as a well positively skewed distribution,
since it has increasing, decreasing, and constant rate function
depending on the shape parameter only, and it has an explicit
expression of the distribution and reliability functions.

Regression analysis of dummy variables with effect code
showed the same results of the analysis of variance table when
they were applied on three fixed model designs. The designs
were: completely randomized, randomized complete blocks and
Latin square. This procedure gave an advantage upon the classic
one, it yield additional information about the relation between the
response and predictors as the regression analysis does, such as:
coefficient of determination, identification of the outliers, also
tackled the missing observations without estimating them.

The reconciliation of one of the time series models with
ARIMA (P, D, Q) S seasonal to the average humidly in Mosul
(1971-2001) has been carried out in this study. Prediction It is reached to the best Models in the
proportional ARIMA (2, 1, 4) 8, because it has the less value
for statistical standard AIC (k), MSE.
The current study, also arrived at to the reconciliation of
seasonal time series models after performance of introduction for
series by making Programs (MATLAB) for it. The method
adopted is Winters' Three Parameters Exponential (Smoothing)
method, method of Holt-Winters Multiplicative and Holt-Winters
Additive.
The third method chosen is the best model of prediction for
every method depending on the same statistic.
Finally, in this paper the best model is reconciliated for the
introduction methods after performance, the difference for every
method and the choice of the best prediction of every method
depending on the same statistical methods.

The work in this paper estimates the simultaneous
equations of the grains for the period (1961-2002).The estimation
necessitate dealing with the variables that have direct effects on
the world prices of the grains and then adding the economic
crises to the system, which is finance and monetary crises,
petrolic shocks, wars, and curtness. For estimation we have used
limit information maximum likelihood (LIML) and K-Class
estimator (K-Class). We depended on the results of the last
method because it is more accurate and efficiently with the economic and statistic theory. The (SAS.9) Package is used to
obtain the results.

This research tackles a forecasting by using Winters' methode
for seasonal time series by using the data which represent the
monthely average of temperature to Mosul city in Iraq for the
period 1985-2000. It is clearly that the method is efficient after
comparing the results of forecasting with the origenal data .

In this research, the Monte Carlo simulation and genetic
algorithm have been carried out on the problem of minimum
variance estimate, algorithm was suggested to find out the
estimate that realizes the minimum variance which its application
leads to a number of resolutions equivalent to the number of
times of generating algorithm including the minimum estimate
and application the Monte Carlo simulation on the same problem to find out random resolutions. This study assured that the
Genetic algorithm is the best to resolve such kinds of problems

This research shows the forecasting using both of ARIMA and
state space models. We firstly predict using ARIMA models, then
we predict again after using ARIMA state space representation.
We consider the MSE as a criterion to show the equivalent of
procedures.