{smcl} {* *! version 1.0.0 01Sep2024}{...} {cmd:help enwei} {hline} {title:Entropy Method} {p 8 14} {title:Title} {p2colset 7 20 20 2}{...} {p2col:{hi:enwei} {hline 2}}Calculation of Weights and Comprehensive Scores Using the Entropy Method{p_end} {p2colreset}{...} {title:description} {p}{cmd:enwei} uses the entropy method to calculate index weights and Comprehensive scores. The output results include entropy, Divergence, weights, composite scores, and individual variable scores. {title:Syntax} {p 8 14 2} {cmd:enwei} {varlist} {cmd:,} {cmdab:o:rder}{cmd:(}{help numlist}{cmd:)} [{cmdab:gen:erate(varname)} {cmdab:dim:ension(varname)} {cmdab:rep:lace} {cmdab:b:iase}{cmd:(}{help numlist}{cmd:)}] {synoptset 26 tabbed}{...} {synopthdr} {synoptline} {p2coldent:* {cmdab:o:rder}{cmd:(}{help numlist}{cmd:)}}{help numlist} is a set of values that indicate the positive or negative direction of the variable, {hi:non-zero} indicates that the corresponding variable is {hi:positive}, and {hi:0} indicates that the corresponding indicator is {hi:negative}. The variables that need to be weighted are v1, v2, v3, v4,{help numlist} are 1, 0, 0, 1, then v1 and v4 are positive variables, v2 and v3 are negative variables.{p_end} {synopt:{cmdab:gen:erate(varname)}}{hi:varname} is the variable name of the Comprehensive score using the entropy method, and the default variable name is {hi:entropy}.{p_end} {synopt:{cmdab:dim:ension(varname)}}{hi:varname} is the variable name prefix of the score of each variable calculated by entropy method. If this parameter is not set, the score of each variable is not generated separately.{p_end} {synopt:{cmdab:rep:lace}}{cmdab:rep:lace} indicates that variables with the same name that already exist in the data will be overwritten.{p_end} {synopt:{cmdab:b:iase}{cmd:(}{help numlist}{cmd:)}}Since one of the observed values must be 0 when using normalization, the amount of translation needs to be set. {help numlist} is a custom translation; If not set, the translation is the reciprocal of the number of samples multiplied by 1000.{p_end} {marker examples}{...} {title:Examples} {pstd}Setup{p_end} {phang2}{cmd:sysuse citytemp4.dta , clear} {p_end} {phang2}{cmd:drop if missing(heatdd)} {p_end} {phang2}{cmd:enwei heatdd cooldd tempjan tempjuly , order(1 0 0 1) gen(I) dim(d) replace} {title:Output the Weights to word} {phang2}{cmd:collect:enwei heatdd cooldd tempjan tempjuly , order(1 0 0 1) gen(I) dim(d) replace} {phang2}{cmd:collect layout (rowname[W]) (colname) (result[W]), name(default)} {phang2}{cmd:collect export "Weights", as(docx) replace} {marker results}{...} {title:enwei results} {pstd} {cmd:enwei} stores the following in {cmd:r()}: {synoptset 15 tabbed}{...} {p2col 5 15 19 2: Matrices}{p_end} {synopt:{cmd:r(OrderM)}}direction{p_end} {synopt:{cmd:r(E)}}Entropy{p_end} {synopt:{cmd:r(D)}}Divergence Coefficient{p_end} {synopt:{cmd:r(W)}}Weights{p_end} {synopt:{cmd:r(Index)}}Comprehensive Score{p_end} {synopt:{cmd:r(DIM)}}the score of each variable{p_end} {title:Authors} {phang}Jiang Qi{p_end} {phang}微信公众号:Zscholar Data Scientist{p_end} {phang}{browse "deeptravonearth@gmail.com":deeptravonearth@gmail.com} {p2colreset}{...}