R语言 glogis包 HICP()函数中文帮助文档(中英文对照)

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HICP(glogis)
HICP()所属R语言包：glogis

                                        Harmonised Index of Consumer Prices (1990–2010, OECD)
                                         消费者物价调和指数（1990-2010年，经济合作与发展组织）

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

Time series data with HICP (Harmonised Index of Consumer Prices) for 21 countries (plus EU) for 1990–2010 as provided by the OECD; and corresponding seasonally adjusted inflation ratios.
加EU）21个国家（2090至10年经济合作与发展组织所提供的和相应的经季节性调整通货膨胀率的时间序列数据，居民消费价格调和指数（HICP）。


用法----------Usage----------


  data("HICP")

  data("hicps")  



格式----------Format----------

Monthly multiple "zooreg" time series with "yearmon" index from Jan 1990 (HICP) or Feb 1990 (hicps) to Dec 2010 for 21 countries (plus EU).
每月多个"zooreg"时间序列与"yearmon"（HICP）1990年2月（hicps）加EU）21个国家（2010年12月指数从1990年1月。


Details

详细信息----------Details----------

HICP contains the raw unadjusted Harmonised Index of Consumer Prices as provided by the OECD from which unadjusted inflation rates can be easily computed (see examples).
HICP包含未经调整的原始未经调整的通胀率，可以很容易地计算（见例子）经济合作与发展组织提供的消费物价调和指数。

As the different countries have rather different seasonal patterns which vary over time (especially in the 2000s), they will typically require seasonal adjustment before modeling. Hence, a seasonally adjusted version of the inflation rate series is provided as hicps, where X-12-ARIMA (version 0.3) has been employed for adjusted. An alternative seasonal adjustment can be easily computed use stl (see examples).
由于不同的国家有不同的模式，随着时间的推移（尤其是在2000年），而不同的季节，他们通常会要求造模前的季节性调整。因此，经季节性调整的通货膨胀率系列hicps，X-12-ARIMA（0.3版）已被雇用调整。另一种季节性调整可以很容易地计算使用stl（参见示例）。


源----------Source----------

Organisation for Economic Co-operation and Development (OECD)
经济合作与发展组织（OECD）

http://stats.oecd.org/



参考文献----------References----------

Wikipedia (2010). "Harmonised Index of Consumer Prices – Wikipedia, The Free Encyclopedia." http://en.wikipedia.org/wiki/Harmonised_Index_of_Consumer_Prices, accessed 2010-06-10.
Windberger T, Zeileis A (2011). Structural Breaks in Inflation Dynamics within the European Monetary Union. Working Paper 2011-12. Working Papers in Economics and Statistics, Research Platform Empirical and Experimental Economics, Universit盲t Innsbruck. http://EconPapers.RePEc.org/RePEc:inn:wpaper:2011-12

实例----------Examples----------


## price series[＃价格系列]
data("HICP", package = "glogis")

## corresponding raw unadjusted inflation rates (in percent)[＃相应的原始未调整通货膨胀率（％）]
hicp <- 100 * diff(log(HICP))

## seasonal adjustment of inflation rates (via STL)[＃经季节性调整的通胀率（通过STL）]
hicps1 <- do.call("merge", lapply(1:ncol(hicp), function(i) {
  z <- na.omit(hicp[,i])
  coredata(z) <- coredata(as.ts(z) - stl(as.ts(z), s.window = 13)$time.series[, "seasonal"])
  z
}))
colnames(hicps1) <- colnames(hicp)

## load X-12-ARIMA adjusted inflation rates[X-12-ARIMA＃负载调整后的通胀率]
data("hicps", package = "glogis")

## compare graphically for one country (Austria)[＃图形比较一个国家（奥地利）]
plot(hicp[, "Austria"], lwd = 2, col = "lightgray")
lines(hicps1[, "Austria"], col = "red")
lines(hicps[, "Austria"], col = "blue")
legend("topleft", c("unadjusted", "STL", "X-12-ARIMA"), lty = c(1, 1, 1),
  col = c("lightgray", "red", "blue"), bty = "n")

## compare graphically across all countries (via lattice)[在所有国家中比较图形化（通过晶格）]
if(require("lattice")) {
trellis.par.set(theme = canonical.theme(color = FALSE))
xyplot(merge(hicp, hicps1, hicps),
  screen = names(hicp)[rep(1:ncol(hicp), 3)],
  col = c("lightgray", "red", "blue")[rep(1:3, each = ncol(hicp))],
  lwd = c(2, 1, 1)[rep(1:3, each = ncol(hicp))])
}



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注：
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