time series 时间序列 | fractional factorial design 部分要因试验设计

作业： 

1) A plot of data from a time series, which shows a cyclical pattern – please show a time series plot and identify the length of the major cycle. 

2) Data from a full factorial or fractional factorial experiment with at least 2 factors – please identify the factors and the dependent variable. It is sufficient to provide me with a small part of the dataset (e.g. 10 records), if the dataset is large.

slides for FFD

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kings <- scan("http://robjhyndman.com/tsdldata/misc/kings.dat",skip=3) kings kingstimeseries <- ts(kings) kingstimeseries # An example is a data set of the number of births per month in New York city, from January 1946 to December 1959 births <- scan("http://robjhyndman.com/tsdldata/data/nybirths.dat") birthstimeseries <- ts(births, frequency=12, start=c(1946,1)) birthstimeseries # souvenir <- scan("http://robjhyndman.com/tsdldata/data/fancy.dat") souvenirtimeseries <- ts(souvenir, frequency=12, start=c(1987,1)) souvenirtimeseries # plot.ts(kingstimeseries) # plot.ts(birthstimeseries) # plot.ts(souvenirtimeseries) # logsouvenirtimeseries <- log(souvenirtimeseries) plot.ts(logsouvenirtimeseries) # library("TTR") birthstimeseriescomponents <- decompose(birthstimeseries) birthstimeseriescomponents$seasonal # get the estimated values of the seasonal component plot(birthstimeseriescomponents) # birthstimeseriescomponents <- decompose(birthstimeseries) birthstimeseriesseasonallyadjusted <- birthstimeseries - birthstimeseriescomponents$seasonal plot(birthstimeseriesseasonallyadjusted)

　　

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#tell where the data come from datafilename="http://personality-project.org/R/datasets/R.appendix1.data" #read the data data.ex1=read.table(datafilename,header=T) #do the analysis aov.ex1 = aov(Alertness~Dosage,data=data.ex1) #show the table summary(aov.ex1)   # 2-way datafilename="http://personality-project.org/r/datasets/R.appendix2.data" #read the data data.ex2=read.table(datafilename,header=T) #show the data data.ex2 #do the analysis aov.ex2 = aov(Alertness~Gender*Dosage,data=data.ex2) #show the summary table summary(aov.ex2)

 

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