小编Ras*_*mus的帖子

我想用ggplot2(v.9)绘制世界地图,如果有信息,它会合并两个部分.以下示例说明:

library(rgdal)
library(ggplot2)
library(maptools)

# Data from http://thematicmapping.org/downloads/world_borders.php.
# Direct link: http://thematicmapping.org/downloads/TM_WORLD_BORDERS_SIMPL-0.3.zip
# Unpack and put the files in a dir 'data'

gpclibPermit()
world.map <- readOGR(dsn="data", layer="TM_WORLD_BORDERS_SIMPL-0.3")
world.ggmap <- fortify(world.map, region = "NAME")

n <- length(unique(world.ggmap$id))
df <- data.frame(id = unique(world.ggmap$id),
                 growth = 4*runif(n),
                 category = factor(sample(1:5, n, replace=T)))

## noise
df[c(sample(1:100,40)),c("growth", "category")] <- NA


ggplot(df, aes(map_id = id)) +
     geom_map(aes(fill = growth, color = category), map =world.ggmap) +
     expand_limits(x = world.ggmap$long, y = world.ggmap$lat) +
     scale_fill_gradient(low = "red", high …

我想在R中进行瓦哈卡分解.我相信,它用于例如劳动经济学来区分解释的方差与不明原因的方差.我无法在R中找到合适的解决方案,而且我不愿意自己创建一个(我可能会搞砸它).

无论如何,这里简要解释了这个过程:

http://en.wikipedia.org/wiki/Ronald_Oaxaca

Stata很幸运,有一个相当不错的包装,但Stata对我来说并不容易.

www.stata.com/meeting/5german/SINNING_stata_presentation.pdf

请注意:我还在R-help上发布了一条消息,但它没有得到回复.我希望也可以在这个列表上发帖.

提前谢谢,Rasmus

编辑:我已经做了以下功能,这似乎产生了错误的答案(urgh).我试图按照上面的Stata链接但它没有按照我的希望:)

oaxaca <- function (fsex,frace1,frace2) {
  ## First we make regresions
  data1 <- subset(l2,sex==fsex & race==frace1)
  data2 <- subset(l2,sex==fsex & race==frace2)

  mindata1 <- subset(cbind(grade,exp,I(exp^2)),sex==fsex & race==frace1)
  mindata2 <- subset(cbind(grade,exp,I(exp^2)),sex==fsex & race==frace2)

  reg1 <- lm(log(wage)~grade+exp+I(exp^2), data=data1)
  reg2 <- lm(log(wage)~grade+exp+I(exp^2), data=data2)

  ## DECOMPOSITION
  ################

  ## Variables
  gap <- mean(log(wage[race==frace1 & sex==fsex]))-mean(log(wage[race==frace2 & sex==fsex]))

  mean1 <- colMeans(mindata1)
  mean2 <- colMeans(mindata2)

  beta1 <- summary(reg1)$coefficients[,1]
  beta2 <- summary(reg2)$coefficients[,1]
  beta1incep <- summary(reg1)$coefficients[1,1]
  beta2incep <- summary(reg2)$coefficients[1,1]
  beta1coef <- summary(reg1)$coefficients[c(2,3,4),1]
  beta2coef …

使用data.tablein R,我试图对除了所选元素之外的子集进行操作.我正在使用by运营商,但我不知道这是否是正确的方法.

这是一个例子.例如对于值Delta在IAH:SNA为(3 + 3)/ 2,其是平均Stops在IAH:SNA一旦Delta已被排除.

library(data.table)
s1 <- "Market   Carrier Stops
IAH:SNA     Delta     1
IAH:SNA     Delta     1
IAH:SNA Southwest     3
IAH:SNA Southwest     3
MSP:CLE Southwest     2
MSP:CLE Southwest     2
MSP:CLE  American     2
MSP:CLE   JetBlue     1"

d <- data.table(read.table(textConnection(s1), header=TRUE))

setkey(d, Carrier, Market)

f <- function(x, y){
         subset(d, !(Carrier %in% x) & Market == y, Stops)[, mean(Stops)]}

d[, s := f(.BY[[1]], …

我通常让hl-line采用稍暗的当前背景.这在编辑缓冲区时效果很好.但是,在某些缓冲区中,例如Org议程和Gnus组缓冲区,我想使用更漂亮的颜色(代替光标).

具体而言,我想改变gnus-hl-line 中hl-line的颜色而不影响其他缓冲区中hl-line的颜色.

(add-hook 'gnus-summary-mode-hook 'gnus-hl-line)
(add-hook 'gnus-group-mode-hook 'gnus-hl-line)

(defun gnus-hl-line ()
  (hl-line-mode 1)
  (set (make-local-variable 'line-move-visual) nil)
  (setq cursor-type nil))

谢谢,

使用Phil的建议的最终解决方案.它大部分时间使用中性线,但有时候大胆的线条很明显,例如在Gnus和Org议程中

;; From emacs-wiki:
(defun shade-color (intensity)
  "print the #rgb color of the background, dimmed according to intensity"
  (interactive "nIntensity of the shade : ")
  (apply 'format "#%02x%02x%02x"
         (mapcar (lambda (x)
                   (if (> (lsh x -8) intensity)
                       (- (lsh x -8) intensity)
                     0))
                 (color-values (cdr (assoc 'background-color (frame-parameters)))))))

;; Default hl
(global-hl-line-mode t)
(make-variable-buffer-local 'global-hl-line-mode)
(set-face-background …