IRAOI JOURNAL OF STATISTICAL SCIENCES

Generalized linear models (GLMs) are generalization of the
linear regression models, which allow fitting regression models
to response variable that is non normal and follows a general
exponential family. The aim of this study is to encourage and
initiate the application of GLMs to predict the maternal and fetal
blood lead level. The inverse Gaussian distribution with inverse
quadratic link function is considered. Four main effects were
significant in the prediction of the maternal blood lead level
(pica, smoking of mother, dairy products intake of mother,
calcium intake of mother), while in the prediction of the fetal
blood lead level two main effects showed significance (dairy
products intake of mother and hemoglobin of mother).

The main purpose of this study is to find out vectors that
can be inserted to the statistical analysis of certain groups of
variables which are formed as a result of a certain condition
depending on categorical data (i.e. Qualitative variable ).
Many statistical models have been discussed to deal with
this condition in order to have a discriminate function or to have
variables by which we can specify the condition gradually.
Depending on the importance of the inserted variable in that
condition, a theorem form of this sensitive variable has been
derived . Some applications have been also used in this paper.

This research includes an idea that takes wide cares in modern
applications through the object of Data Mining which is called
Temporal Sequences. An investment of mathematical model
known as Hidden Markov Model, of modeling Temporal
Sequences. This research deals with an application combining
between mathematics, computer and music. The problem of
recognition of musical ladders is studied by using Hidden
Markov Model, Some national songs are studied and modeled
through this model. After making use of the computer for the
songs under study, a result was reached to know a musical ladder
which is used in national songs

In this research a new method was proposed to estimate the
delay time. Which can be used to determine the relationship
between the input and output of the series, this means that after
each time interval, the input is affected by the output.
The advantages of this method are the simplicity and the basic
calculations in linear and nonlinear transformations. The
proposed technique was found by examining the greatest
expansion from the unit line in the impacted space

This research concentrates on the application of the
Genetic Algorithm (GA) which is considered as an artificial
search method on some of the Inventory Models. More than one
which were suggested algorithm led to a number of solutions
equal to the number of algorithm generation ,one of them was
the optimal solution during a specified period of time

his Paper is concerned with the synchronizing between
numbers of dynamic linear system models with different
parameters with their two different kinds. The first kind
represented the equation error model which included ARMAX
and ARX, also the second kind was the output error model which
contained BJ and OE , and, another state space models, After the
application of the above models on the real data ,the comparison
has been done, we choose the ARX(1,7,3) and the state space
model with 4 parameters which gave the minimum statistical criteria. These two models are also used in forecasting and
another comparison has been done between two forecasted
models, and we conclude that the forecasted dynamic linear
system model is the best which gave the minimum statistical
criteria

zero - one programming case from integer linear
programming where the variable's are equal to zero or one, the
decision factor uses this kind from programming when he meets
him problems of the kind yes or no.
The stochastic zero-one programming construction formed is
used when one or all parameters of model(cj ,b i ,aij ) are random
variable taken mathematical distribution.
In this research we discuss stochastic zero-one programming
problem where (aij ) random variable (construction and solution)
and use it in practical application on some vegetative crops in
Iraq.

The research is dedicated in the study to time series and the
ability of using fuzzy logic with it in order to develop
forecasting approaches. In this research ,the time series
(Autoregressive model) are linked with fuzzy logic in order to
get on the Parameters of fuzzy time series models (fuzzy logic
Autoregressive model),and applied that on the data of daily
mistakes rates in charges production. The fuzzy Autoregressive
model of time series gave forecasting more sutiable than those
given by Autoregressive model.

The aim of this research is to find a new separated ratio
estimator in the stratified random sampling ,three other
estimators are compared with the new separated ratio estimator ,
namely : ordinary separated ratio estimator , combined ratio
estimator, and the suggested ratio estimator by ( Kadilar & Cingi
; 2005 ) . Using the (MSE) as a comparative criterion , we proved
that our proposal estimator has more precision than the others .
Many numerical and simulation examples have been applied .

The work in this paper is a diagnosis of three types of
unusual observations in multiple regression, the outlier
observation is diagnostic by using Boxplot & studentized residuals, Diagnostic leverage points by using (Hat matrix) , &
diagnostic of the influence observations by using (dfbeta).
In practice the work is comparing the effects of omitting
outlier observations in the normal distribution of the residuals to
the equation which is building to the Thalassaemia disease and
Treating the multicollinearity by omitting some variables and
using ridge regression, getting a good model agrees with the
viewing of medicine by using (SAS.9) package.

The research deals with the most important specific
development of the traditional mathematical programming (MP) and
shows the mathematical programming with multi-objective (MOMP)
which forms the vertebral column in application of Multi-Criteria
Decision Making (MCDM), Decision Support System (DSS),
operations research / management science (OR/MS). After studying these new models and tools and their uses, the
researcher chose Global Criterion Method to study it concept and
properties, limitation and stages of the solution to achieve the
algorithm and the flow-chart of it, and using the Global Criterion
Method to obtain the best feasible final solutions to constrained
decision, linear, multiple objective problem without any priority or
weighted.
Finally, the study concludes too many feasible solutions which
are called, non-dominated solutions to the application of a case study
and comparison with the results of using other models

This research suggested a new heuristic method for solving
the n-jobs, m- machines flow shop scheduling problem to
minimize total completion time. This method was compared with
The (NEH) method for data generated by using (matlab) and
showed high efficiency and easy to use.