IRAOI JOURNAL OF STATISTICAL SCIENCES

This study deals with the famous trackers named Kalman and
extended Kalman filters. This is introduced by describing the
state space representation approach to model the target system. A
modification to the state prediction equation of Kalman and
extended Kalman filters is given in order to offer an ability of
multi-step ahead prediction of the target future position. The
problem of missed measurements, with different percentages of
missing, is studied and a method to estimate these missed
measurements is then suggested. Some simulation experiments
are performed and indicated that Kalman filtering techniques are
promising when they deal with target tracking problem

We present in this paper Bays method by using Jeffery
prior information and new Bayesian using extension of Jeffery
prior information for estimating the parameter of exponential
distribution and survival function . It has been shown from the
computational results that the method which gives the best
estimates is an extension of Jeffery prior information

The importance of Transfer Function Model comes from
its use in prediction . The model has been constructed with
multi-inputs because of the importance of multi-input in
contructing models. Such multi-inputs give better results because
the more effective inputs are used , the more precise are the
results.In order to get the best prediction , the study studies the
construction of transfer function model by black box models This method consists of constructing many models for the
basic models of the black box Model,namely (ARX, ARMAX,
BJ, OE ). The model which gave the best result was the model
"BJ" depending , for comparison , on a group of statistical and
geometrical standards .

A comparative study between linear transfer models of low
order and ARX model of high order depends on spatial series.
The research includes a comparison between efficiency of
the different linear transfer function f stationary time – spatial
series with low order models ( ARX11k , ARMAX2221 ,O.E221
, B.J22221 , pss1 ) and high order ARX model according to the
percentage rate of coincidence of the model to the data . The
comparison is made on a spatial – time series which shows the effect resulted on the biological factors of the soil as a
consequence of changes in the chemical factors on one hand and
physical factors on the other, and the two factors all are together
as an input–output model ( multiple–uni ) in one time and
(multiple–multiple) on another time . It appears that ARX models
of high order has a high percentage fit compared with the transfer
models of low order

In This paper, we suggest two approaches for the parallel
tangent (PARTAN) method. First is to combine PARTAN
method with Perry algorithm and second is to combine PARTAN
method with Al-Bayati-Ahmed, 1996 algorithm. The new
suggested methods are tested to solve unconstrained optimization
problems by using statistical tests and the results of the new
suggested methods are better than the original PARTAN method
with respect to time and the accuracy.

The study of time series is one of first important subjects
especially with study of analysis behavior of different
phenomenon’s and discussed it throw the historical in different
period to forecasting.
The initial aims of statistical sciences to know the behavior
of feature search, we found each day throw the media the care of
different economic and wether forecasting. The aim of this
search to compare Adaptive Filtering and Artificial Neural
Networks to forecasting of time series models.

n this paper, we shall try to determine outliers and
pinpoint its source of existence by using Box-Whisker
plots technique which is an effective approach to detect
and treat outliers. Thus the researchers prove that the Box-
Whisker-Plot is the most effective method among other
methods used in this research which is the hypothesis of
the paper.

This study deals with hidden Markov models . These
models consist of sets of finite states , each one of them is
associated with a probability distribution . The transition among
the states is governed by a set of probabilities namely “
Transition probabilities ” . In general , the final observation
produced according to the associated probability , where there is
only probability production instead of a clear visible states .
Therefore , these states are described as hidden
The basic problems for hidden Markov models (HMMs) are :
- The probability account for the observation sequence (O)
when the model is given = (A , B , ) , i.e. P(O|) Where :
A = The state transition probabilities .
B = The observation probability matrix .
= The initial state distribution .
- Choosing the optimal state of the sequence for hidden
Markov process.
- Finding the model = (A , B , ) which has the greatest
probability , i.e. re-estimating the model to maximiz P(O|) .
in addition to its results

The idea of this project is based on programming the functions of
DirectX, which will connect the last one with the windows, this work is
needed because DirectX deals with the hardware and the buffers of the
memory while the windows does not directly deal with it.
The work focuses on programming the DirectPlay function, which is
considered as an interface programming to guarantee the arrival of the
applications to the communication services.
DirectPlay supports the facilities of connecting the game with the
internet directly by the Modem Link or indirectly by the Ethernet. Actually
the game becomes more flexible and enjoying if it is played against a real
player (or another user of the computer) instead of playing with the
computer itself. Also DirectPlay supports a group of users connected with
each other in an active way at the same time (for example, the Internet
chatting or Ethernet chatting).
In this work, an Ethernet chatting is done by using a Client/Server
applications to see the working of DirectPlay, then, we try to use an active
and strong language to make this is possible, and therefor we use the Visual
C++ language

This paper studies a time series for the number of infection
of Tuberculosis of the lungs as a Markov – chain. We have made
hypotheses concerning the number of infections in order to set
the problem according to Markov-chain. Then I’ll try to find the
characteristic of this chain that proved to be non-ergodic. I found
the absorbing probability for the transient state and the expected
absorbing time.

In this paper, a simulation has been done for the radial basis
model of sunspot time series . Chaotic analysis of the
simulated data from model, and the study of the chaotic behavior
for such a model indicates that the model is chaotic and the
sunspot time series is chaos .

The secret Electronic Mail messages encounter many
problems that causes hacking or modifies it, therefore is
necessary to find active ways, to keep it out of hackers and
intruders, hiding technique was applied to satisfying that.
The Traditional ways depend on hiding secret message data
in between words or statements of carrier message, after dividing
its characters values in to sequence of bits, was leaving one or
two spaces depending on hided bit value (0 or 1).
In this research, a new concept was applied to create only
one space in this two cases, this method carried out higher
performance than traditional methods, there is no perceptual
hiding for hackers and intruders, and satisfied full matching in
figure and size of carrier message before and after hiding

In this research, we compared restricted least squares )ˆ( RLIU

with restricted Liu estimator ( )RLS
ˆ . by using (MSE) criterion
in the existence of multicollinearity. We found that
restricted Liu estimator is the best in comparison