课后习题答案#x2d;时间序列分析及应用（R语言原书第2版）.docxVIP

Solutions Manual to Accompany Time Series Analysis with Applications in R, Second Edition by Jonathan D. Cryer and Kung-Sik Chan Solutions by Jonathan Cryer and Xuemiao Hao, updated 7/28/08 Chapter 1 Exercise 1.1 Use software to produce the time series plot shown in Exhibit (1.2), page 2. The following R code will produce the graph. library(TSA); data(larain)； win.graph(width=3/height=3,pointsize=8) a plot(y=larain,x=zlag(larain,ylab=1Inches *,xlab=Previous Year Inches} Exercise 1.2 Produce the time series plot displayed in Exhibit (1.3), page 3. Use the R code data(color)； plot(color,ylab=Color Property，丨Baluh，,typ皂■) Exercise 1.3 Simulate a completely random process of length 48 with independent, nomial values. Repeat this exercise several limes with a new simulation, that is. a new seed, each time. plot (ts rnoxm\ ln=4 8)), type= *0*) # l￡ you repeat this command R will use a new * random numbers1* each time. If you want to reproduce the same simulation first use the command set.seed(#######?# where is an integer of your choice. Exercise 1.4 Simulate a completely random process of length 48 with independent, chi-square dislribuled values each with 2 degrees of freedom. Use the same R code as in the solution of Exercise 13 but replace morTn(n-48) with rchisq (n?48 z df ?2). Exercise IS Simulate a completely random process of length 48 wilh independent, /-distributed values each with 5 degrees of freedom. Conslrucl (he time series plot. Use the same R code as in lhe solution of Exercise 1.3 but replace rnormn-48) with rt(0^48, df ?5). Exercise 1.6 Construct a Lime series plot with monthly plotting symbols for the Dubuque temperature series as in Exhibit (1.7). page 6. (Make the plot full screen so that you can see all of detail.) ..— ?.■ ■一 .■ — data(tempdub)； plot(tempdubrylab-Temperature) pointe(ystempdub^xstime(tempdub). pch=as.vector(season(tempdub}) Chapter 2 Exercise 2.1 Suppose E(X) = 2, Var[X} = 9, E(K) = 0. VariY) = 4. and CorriX.Y) = 0.25. Find: Var(X +