作者查詢 / gsuper
作者 gsuper 在 PTT [ Statistics ] 看板的留言(推文), 共1226則
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收起看板(734)
1F→:看不懂你在幹嗎09/11 17:57
2F→:不過流程如下 1.excel檔案存成 tab 隔開的 txt file09/11 17:58
3F→:2. read.delim("xxx.txt",sep="\t",header=TRUE)09/11 17:58
4F→:3. 要切掉 column , 移動資料 , 矩陣轉置都屬於資料處理09/11 17:59
5F→:不要跟前面的東西混再一起09/11 17:59
10F→:眾數很不理想 因為資料為連續 or 資料密集度不足時很難用09/10 12:13
2F→:資工的話 可計算N1每群的重心 在找出一個N1的centroide09/04 13:36
3F→:然後也找出N2的centroide , 最後再計算兩者的 distance09/04 13:37
4F→:然後可以將 N1和N2內全部的 single points09/04 13:39
5F→:計算 N1*N2 全部的 distance 做為 reference distribution09/04 13:39
6F→:重心的計算 若資料約有 5% 的 outlier , 可選5% trim mean09/04 13:43
7F→:但若資料若有很嚴重的不均勻度 這種簡單的概念就不太適用09/04 13:44
9F→:靠 permutation 做出來的 ref distribution 應該可以無視09/04 19:51
10F→:事前的分佈 因為理論上 sampling dis 應該是常態09/04 19:51
11F→:然後你的 distance 是一種 test statastics09/04 19:52
15F→:我會考慮參考 meta-analysis 的 random effect 公式去計算09/09 18:18
16F→:處理第一群中的 N1 小群的問題09/09 18:18
17F→:不過這樣搞 , 要找 ref distribution 就難了09/09 18:18
10F推:1的話 我都是分成兩張矩陣 A & B08/22 17:02
11F→:然後另行加兩個 columns 作為 "index"08/22 17:11
12F→:不管怎麼橋 最後用 merge.data.frame 就可以還原08/22 17:11
1F→:用全域變數 a<<-10 ; 就可以把裡面的變數直接存在外面08/20 23:31
2F→:除非你要寫遞迴 不然用全域變數很方便08/20 23:32
3F→:一次解決你的三個問題08/20 23:33
1F→:spss無誤 應該沒有更簡單的了08/18 20:04
2F→:不然 R , SAS , matlab 都要會基礎 coding08/18 20:06
8F→:excel 也很難吧 , 要會寫 visual basic 的巨集才能跑迴圈08/19 17:27
9F→:我Lab有人這樣用 速度慢到看了快吐血08/19 17:27
3F→:另一種較不直覺的寫法 sum(!duplicated(x))08/14 12:54
1F→:倒數第二段是說ANOVA對常態性依賴太重,考量到穩健性08/13 21:57
2F→:改用Kruskal-Wallis的無母數統計(類似anova但改用中位數)08/13 21:58
3F→:最後一段是說XYZ組別之間的變異數不能差異的太離譜08/13 22:02
4F→:所以去檢定變異數同質性,跟之前檢定XYZ的常態性類似08/13 22:02
5F→:都是為了說服讀者他做的 F-test 可信,因為這些都是基本假設08/13 22:03
6F→:所以作者應該同時有提供Anova&Kruskal-Wallis兩種檢定結果08/13 22:04
7F→:看看你是否總之是會相信這樣08/13 22:04
1F→:x[order(x[,dim(x)[2]]),][126:dim(x)[1]-125,]08/09 16:59
2F→:注意 class(x[,dim(x)[2]]) 必須是數值型變數08/09 17:01
3F→:x[order(x[,dim(x)[2]]),][126:(dim(x)[1]-125),]08/09 17:01
4F→:剛剛第一航少寫個括號08/09 17:02
1F→:R還是自學比較好 開課1.教基礎程式邏輯 2.教統計 3.教R語法08/07 20:54
2F→:整個就是駁雜08/07 20:54