Use R within Mathematica

Needs["RLink`"]

(* For Mac and MMA 10*)

SetEnvironment[ "DYLD_LIBRARY_PATH" ->"/Library/Frameworks/R.framework/Resources/lib"]
InstallR["RHomeLocation" -> "/Library/Frameworks/R.framework/Resources", "RVersion" -> 3];
REvaluate["R.version.string"]

(* Load packages*)

REvaluate["library(psych);"]
REvaluate["library(nortest);"]
REvaluate["library(GenABEL);"]

(* 因素分析，主成分法萃取，變異及大化法轉軸 *)

myfac=Map[REvaluate["{xx<-principal(iris[,1:4],nfactors="<>ToString[#]<>",
rotate=\"varimax\");xx$loadings}"]&,{2,3,4}];
myfac

(* 輸出因素負荷矩陣 *)

Reverse[SortBy[myfac[[1,1]],{#[[1]],#[[2]]}&]]//TableForm
TableForm/@myfac[[All,1]]


(* 因素分析資料*) 

fadata = {
{1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 4, 5, 6}, 
{1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 3, 4, 3, 3, 3, 4, 6, 5}, 
{3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5, 4, 6}, 
{3, 3, 4, 3, 3, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 5, 6, 4}, 
{1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 6, 4, 5}, 
{1, 1, 1, 2, 1, 3, 3, 3, 4, 3, 1, 1, 1, 2, 1, 6, 5, 4}};

(* 定義資料*)

RSet["factor", Transpose@fadata];

(* 在R中計算相關係數矩陣，傳回MMA小數後四捨五入 *)

Round[REvaluate["cor(factor)"], 0.0001] // MatrixForm

(* 因素分析 *)

REvaluate["factanal(factor, factors = 3)$loadings"]

(* 輸出因素負荷矩陣 *)

TableForm[#[[1]], TableHeadings -> {None, #[[-1, -1, -1, -1]]}] & /@ 
{REvaluate["factanal(factor, factors = 3)$loadings"]} // Column
 
 
(* 迴歸分析 *)

REvaluate["{
data(iris)
reg <- lm( Sepal.Length ~ Species, data=iris )
summary.text <- capture.output(print( summary(reg)) )
}"]

StringJoin@Riffle[#, "\n"] &@REvaluate["{
data(iris)
reg <- lm( Sepal.Length ~ Species, data=iris )
summary.text <- capture.output(print( summary(reg)) )
}"]
 
(* 產生常態隨機變數 *)

mydata=REvaluate["rnorm(100,mean=0,sd=1)"]&/@Range[100]; 

(* MMA次數分配 *)

\[ScriptCapitalD] = HistogramDistribution[mydata[[1]]]  

(* MMA PDF & CDF *)

GraphicsRow[DiscretePlot[#[\[ScriptCapitalD], x], {x, -4, 4, .01}, 
PlotLabel -> #] & /@ {PDF, CDF}]

(* shapiro test, ks.test *)

shapiro[data_] := Block[{temp},
  RSet["temp", data];
  REvaluate[
 "{xx=shapiro.test(temp); yy=ks.test(temp,\"pnorm\",0,1); zz=lillie.test(temp); 
 c(xx$statistic,xx$p.value,yy$statistic,yy$p.value,zz$statistic,zz$p.value)}"][[1]] ]
 
RSet["rn1", RandomReal[{0, 10}, 1000]];
rn2 = RandomReal[NormalDistribution[0, 1], 1000];
REvaluate["rntransform(rn1)"] // Short
Histogram[#, Frame -> True] & /@ {rn2, REvaluate["rntransform(rn1)"]}
ShapiroWilkTest[#, {"TestStatistic", "PValue"}] & /@ {rn2, REvaluate["rntransform(rn1)"]} 


(* 利用RCurl擷取網路資料 *)

gosspost[n_]:=REvaluate["
{library(RCurl);
curl<-getCurlHandle();
curlSetOpt(cookie=\"over18=1\",followlocation=TRUE,curl=curl);
url<-\"https://www.ptt.cc/bbs/Gossiping/index" <> ToString[n] <> 
".html\";
html<-getURL(url,curl=curl)
}"][[1]];

Gossiping = 
  Cases[ImportString[
StringReplace[gosspost[#], {"\n" -> "", "\t" -> ""}], 
"XMLObject"],
  XMLElement[
 "div", {"class" -> "r-ent"}, {XMLElement[
"div", {"class" -> "nrec"}, {XMLElement[
  "span", {"class" -> "hl f2"}, {_}]}], 
  XMLElement["div", {"class" -> "mark"}, {}], 
  XMLElement[
"div", {"class" -> "title"}, {XMLElement[
  "a", {"shape" -> "rect", 
"href" -> postlink_}, {posttile_}]}], 
  XMLElement[
"div", {"class" -> "meta"}, {XMLElement[
  "div", {"class" -> "date"}, {_}], 
 XMLElement[
  "div", {"class" -> "author"}, {author_}]}]}] :> {postlink, 
 posttile, author},
  Infinity] & /@ Range[20861, 20862, 1];
  
Flatten[Gossiping, 1] // TableForm  

Tags: Mathematica 教學, Mathematica 教學 程式

• 編輯文章
• 此文章網址
• 轉寄此文章
• 目前有0 意見