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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)
3F→:事後處理就好啦 矩陣[is.na(矩陣)] <- 其他符號11/03 13:24
3F→:data[data[,"V1"]==1,] <- "Apple" ; 寫六行10/29 14:36
4F→:data[data[,"V1"]==1,"V1"] <- "Apple" ; 上面那行不對10/29 14:36
1F→:這個是很高階的東西 要循序漸進10/22 18:47
2F→:"Making Sense of Odds and Odds Ratios" 從這篇開始吧10/22 18:48
3F→:http://tinyurl.com/98znjv910/22 18:49
4F→:上面那個是 Part I , II , III , IV10/22 18:50
13F→:我不是糖 是超級10/23 13:20
1F→:vec <- c(5,4,6,3,1,2)10/20 17:19
2F→:apply(你的矩陣,1,function(tmp){sum(tmp!=vec)==0})10/20 17:19
6F→:回圈 , 改 vec 的參數10/21 20:03
1F→:while (abs(rt-lt)>1E-6) 這附近檢查看看10/21 21:14
8F→:去看 兩個平均值相除的結果有沒有 >2或<0.510/21 16:50
3F→:u是population dis , u[,1]是sample dis , y是sampling dis10/13 22:31
4F→:統計課本前幾章應會對這三種分佈詳加定義10/13 22:33
3F推:電影應該錯09/20 20:43
4F→:假設最初在 training 電腦時 , 給它13個選項(1~13) , 會是09/20 20:46
5F→:多元分佈 , 因此電腦題出的解答總合必須是 109/20 20:47
6F→:另一種是當初在 training 電腦時 , 對每張牌提出 2 個選項09/20 20:48
7F→:比方說猜它是 A士 或 不是A士 , 所以會得到13個2元分佈09/20 20:49
8F→:這樣加起來就會破百 , 但不是非常合理09/20 20:50
9F→:除非機器對攝影機的影像分析 , 對某些數字會有嚴重缺陷09/20 20:50
10F→:否則應該是採用多元分佈 , 讓電腦去猜每張牌 1~13 共13選項09/20 20:51
11F→:ps. 13個2元分佈應該可以做成一個混合分佈09/20 20:52
12F→:理論上若 13 種號碼的猜中機率差不多 , 會趨近多元分佈09/20 20:53
13F→:ps2. 還有種可能是做某些 adjusting09/20 20:54
14F→:比方說小刀哥把牌拉開 0.2mm 或 0.4mm 會得出不同機率09/20 20:55
15F→:或者是咪排的角度不同等等的09/20 20:55
1F噓:你的其中一些問題 在你的上一篇我有給過你指令09/19 11:17
2F→:DATA<-matrix(NA,50,2000);09/18 13:36
3F→:for(g in 1:2000){DATA[,g]<-rnorm(50)}09/18 13:36
4F→:x<-cor(DATA);x[abs(x)==1]<-0;09/18 13:36
5F→:y<-abs(x)==max(x) ;09/18 13:36
6F→:which(colSums(y)>0) ; which(rowSums(y)>0);09/18 13:37
7F→:Assume 只有一個最大值 & 最大值不可能為 109/18 13:38
8F→:其它還有些手工的部分就自己學吧09/18 13:38