NORMAL RESIDUALS IS ONE OF THE USUAL ASSUMPTION OF AUTOREGRESSIVE MODELS BUT IN PRACTICE WE FACED NON-NEGATIVE RESIDUALS CASE. IN THIS PAPER WE CONSIDER TWO AUTOREGRESSIVE MODELS WITH GAMMA AND WEIBULL RESIDUALS AS COMPETING MODELS AND DERIVE MODIFIED MAXIMUM LIKELIHOOD ESTIMATORS OF PARAMETER OF THESE MODELS. ALSO BY USING SIMULATION, IT IS SHOWN THAT Kullback-Leibler INFORMATION AS AN OPTIMUM MODEL SELECTION CRITERION IN SET OF COMPETING MODELS FOR DATA THAT GENERATED OF AUTOREGRESSIVE WITH NON-NEGATIVE RESIDUALS ARE APPROPRIATE.

IN THIS ARTICLE, WE CONSTRUCTED A GOODNESS-OF-_T TEST STATISTIC BASED ON Kullback- Leibler INFORMATION FOR EXPONENTIAL DISTRIBUTION BY USING MAXIMUM LIKELIHOOD ESTIMATE OF THE MODEL PARAMETER. A MONTE CARLO SIMULATION IS PERFORMED TO EVALUATE THE POWER OF THE PROPOSED TEST FOR SEVERAL ALTERNATIVES UNDER DI_ERENT SAMPLE SIZES AND PROGRES- SIVE _RST-FAILURE CENSORING SCHEMES. ...

STATISTICAL MODELING IS A CRUCIAL ISSUE IN SCIENTIFIC DATA ANALYSIS. MODELS ARE USED TO REPRESENT STOCHASTIC STRUCTURES, PREDICT FUTURE BEHAVIOUR, AND EXTRACT USFUL INFORMATION FROM DATA. MANY RESEARCHERS IN MEDICINE, ENGINEERING, SOCIAL SCIENCES AND ECONOMICS, PLANNING, MANAGEMENT, GEOGRAPHY, PHYSICS, MATHEMATICS, STATISTICS AND OTHER SCIENCES TO CONDUCT AN INVESTIGATION, ACCORDING TO THE DATA AVAILABLE FOR THE TEST UNDER CONSIDERATION REQUIRES NOTICE TO THE SELECTION CRITERIA MODELS ARE SUITABLE. WHEN THE CORRECT MODEL IS UNKNOWN, THE RESEARCHERS PROPOSED A FAMILY OF MODELS TO FIND THE CLOSEST MODEL IS THE CORRECT MODEL, IT IS NECESSARY TO DEFINE A CRITERION FOR UNBIASED INFORMATION. THIS PAPER EXAMINES THE INFORMATION CRITERIA AIC AND AICC DEALS.

THIS PAPER ADDRESSES THE ISSUE OF PROGRESS RECOGNITION FROM HIGH DETERMINATION REMOTELY DETECTED PICTURES AND ITS APPLICATION ON ROAD HARM EXTRACTION IF THERE SHOULD BE AN OCCURRENCE OF SIGNIFICANT CALAMITY IN CASE STUDY OF IRAN ROADS.THE PROPOSED SYSTEM DEPENDS ON THE MULTI -SCALE PICTURE DIVISION UTILIZING THE HAAR WAVELET AS A PART OF REQUEST TO CHARACTERIZE THE PROPER UNIT OF EXAMINATION FOR THE CORRELATION STEP. THE Kullback-Leibler DISPARITY IS THEN CONNECTED AS A COMPARABILITY ESTIMATION TO RECOGNIZE CHANGED AREAS. THIS PROCEDURE IS ADJUSTED TO ILLUMINATE THE ROAD HARM EXTRACTION ISSUE BY APPLYING THE DEMPSTER-SHAFER HYPOTHESIS (DST). THE PICTURES GAINED AMID THE CAR INJURIES ACCIDENT THAT HITS IRAN’S ROADS FROM 2010 TO 2015 ARE UTILIZED AS A PART OF THE EXPERIMENTATIONS AND GOT RESULTS EXHIBIT THE PRECISION AND THE PRODUCTIVITY OF THE PORTRAYED TECHNIQUE.