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Information Seminar Paper

Title

CONSIDERING THE INFORMATION CRITERIA

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  -

Abstract

 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.

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    APA: Copy

    Ghahramani, Masume, & SHAMS, MEHDI. (2014). CONSIDERING THE INFORMATION CRITERIA. CONFERENCE ON COMPUTATIONAL GROUP THEORY, COMPUTATIONAL NUMBER THEORY AND APPLICATIONS. SID. https://sid.ir/paper/930325/en

    Vancouver: Copy

    Ghahramani Masume, SHAMS MEHDI. CONSIDERING THE INFORMATION CRITERIA. 2014. Available from: https://sid.ir/paper/930325/en

    IEEE: Copy

    Masume Ghahramani, and MEHDI SHAMS, “CONSIDERING THE INFORMATION CRITERIA,” presented at the CONFERENCE ON COMPUTATIONAL GROUP THEORY, COMPUTATIONAL NUMBER THEORY AND APPLICATIONS. 2014, [Online]. Available: https://sid.ir/paper/930325/en

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