tailieunhanh - Comparison of Newton-Raphson algorithm and maxLik function

Our main objective is in antagonizing the performance of two approaches: The Newton-Raphson (N-R) algorithm and maxLik function in the statistical software R to obtain optimization roots of estimating functions. | VOLUME 2 I ISSUE 4 I 2018 I December Comparison of Newton-Raphson Algorithm AND MaxLik Function Kim-Hung PHO1 Vu-Thanh NGUYEN2 Faculty of Mathematics and Statistics Ton Due Thang University Ho Chi Minh City Vietnam 2Faculty of Mathematics and Statistics University of Natural Sciences Ho Chi Minh City Vietnam Corrcsponding Author Kim-Hung PHO Email phokimhung@. vn Received 04-Dcccmbcr-2018 accepted 22-January-2019 published 25-January-2019 DOI http Abstract. Our main objective is in antagonizing the performance of two approaches the Newton-Raphson N-R algorithm and maxLik function in the statistical software R to obtain optimization roots of estimating functions. We present the approach of algorithms examples and discussing about two approaches in detail. Besides we prove that the N-R algorithm can perform if our data set contain missing values while maxLik function cannot execute in this situation. In addition we also compare the results as well as the time to run code to output the result of two approaches through an example is introduced in . Keywords Newton-Raphson algorithm maxLik function optimization comparison. 1. Introduction In statistical inference and applied mathematics estimating functions play an extremely vital position in researches. If having the estimating function we can execute some of approaches to figure out this issue. Comprehensive theory and its applications can be obtained from numerous reference books on statistics. In Godlambc presented about esti mating functions in which a function includes the data set and parameters need to be estimated. An overview the estimating function can be described by H with provided that H data f 0 where f 2 Ỷ and Ỷ is a parameter space. The issues arc associated with finding an optimization root to estimating functions arc exceedingly crucial in several areas such as statistical inferences mathematics technology and economics etc. Therefore it is extremely .