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雷达卡
Dear
The code I copied from http://faculty.chicagobooth.edu/ ... oTS/ch3Rscripts.txt and output are as follows
Coulld you please help fix the issue such as[Error: could not find function 'backtest']. Thanks
================================================================================
### Chapter 3 ####
### Petro Price
da=read.table("C:/Downloads/ch3data/w-petroprice.txt",header=T)
da1=read.table("C:/Downloads/ch3data/w-gasoline.txt")
pgs=log(da1[,1])
pus=log(da$US)
tdx=c(1:717)/52+1997 # calendar time
par(mfcol=c(2,1))
plot(tdx,pgs,xlab='year',ylab='ln(price)',type='l')
title(main='(a) Gasoline')
plot(tdx,pus,xlab='year',ylab='ln(price)',type='l')
title(main='(b) Crude oil')
dpgs=diff(pgs)
acf(dpgs,lag=20)
pacf(dpgs,lag=20)
m1=ar(diff(pgs),method='mle')
m1$order
t.test(dpgs)
m1=arima(dpgs,order=c(5,0,0),include.mean=F)
m1
m1=arima(dpgs,order=c(5,0,0),include.mean=F,fixed=c(NA,NA,NA,0,NA))
m1
tsdiag(m1,gof=20)
dpus=diff(pus)
m3=lm(dpgs~-1+dpus)
summary(m3)
acf(m3$residuals,lag=20)
pacf(m3$residuals,lag=20)
m4=ar(m3$residuals,method='mle')
m4$order
m4=arima(dpgs,order=c(6,0,0),include.mean=F,xreg=dpus)
m4
m4=arima(dpgs,order=c(5,0,0),include.mean=F,xreg=dpus)
m4
m4=arima(dpgs,order=c(5,0,0),include.mean=F,xreg=dpus,fixed=c(NA,NA,NA,0,NA,NA))
m4
tsdiag(m4,gof=20)
c1=c(NA,NA,NA,0,NA)
pm1=backtest(m1,dpgs,316,1,fixed=c1,inc.mean=F)
c4=c(NA,NA,NA,0,NA,NA)
pm4=backtest(m4,dpgs,316,1,xre=dpus,inc.mean=F,fixed=c4)
tdx=tdx[2:717]
pm4fit=dpgs[317:716]-pm4$error
pm1fit=dpgs[317:716]-pm1$error
plot(tdx[317:716],dpgs[317:716],xlab='year',ylab='growth',type='l')
points(tdx[317:716],pm1fit,pch='*')
plot(tdx[317:716],dpgs[317:716],xlab='year',ylab='growth',type='l')
points(tdx[317:716],pm4fit,pch='*')
m6=lm(dpgs[2:716]~-1+dpus[1:715])
summary(m6)
acf(m6$residuals,lag=20)
pacf(m6$residuals,lag=20)
m7=ar(m6$residuals,method='mle')
m7$order
m7=arima(dpgs[2:716],order=c(9,0,0),include.mean=F,xreg=dpus[1:715])
m7
m7=arima(dpgs[2:716],order=c(9,0,0),include.mean=F,xreg=dpus[1:715],fixed=c(NA,NA,NA,0,NA,0,0,0,NA,NA))
m7
tsdiag(m7,gof=20)
c7=c(NA,NA,NA,0,NA,0,0,0,NA,NA)
pm7=backtest(m7,dpgs[2:716],315,1,xre=dpus[1:715],inc.mean=F,fixed=c7)
======================================================
R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.
> ### Chapter 3 ####
> ### Petro Price
> da=read.table("C:/Downloads/ch3data/w-petroprice.txt",header=T)
> da1=read.table("C:/Downloads/ch3data/w-gasoline.txt")
> pgs=log(da1[,1])
> pus=log(da$US)
> tdx=c(1:717)/52+1997 # calendar time
> par(mfcol=c(2,1))
> plot(tdx,pgs,xlab='year',ylab='ln(price)',type='l')
> title(main='(a) Gasoline')
> plot(tdx,pus,xlab='year',ylab='ln(price)',type='l')
> title(main='(b) Crude oil')
> dpgs=diff(pgs)
> acf(dpgs,lag=20)
> pacf(dpgs,lag=20)
> m1=ar(diff(pgs),method='mle')
> m1$order
[1] 5
> t.test(dpgs)
One Sample t-test
data: dpgs
t = 1.3062, df = 715, p-value = 0.1919
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
-0.0005536374 0.0027549956
sample estimates:
mean of x
0.001100679
> m1=arima(dpgs,order=c(5,0,0),include.mean=F)
> m1
Call:
arima(x = dpgs, order = c(5, 0, 0), include.mean = F)
Coefficients:
ar1 ar2 ar3 ar4 ar5
0.5073 0.0788 0.1355 -0.0360 -0.0862
s.e. 0.0372 0.0417 0.0415 0.0417 0.0372
sigma^2 estimated as 0.0003262: log likelihood = 1857.85, aic = -3703.71
> m1=arima(dpgs,order=c(5,0,0),include.mean=F,fixed=c(NA,NA,NA,0,NA))
Warning message:
In arima(dpgs, order = c(5, 0, 0), include.mean = F, fixed = c(NA, :
some AR parameters were fixed: setting transform.pars = FALSE
> m1
Call:
arima(x = dpgs, order = c(5, 0, 0), include.mean = F, fixed = c(NA, NA, NA,
0, NA))
Coefficients:
ar1 ar2 ar3 ar4 ar5
0.5036 0.0789 0.1220 0 -0.1009
s.e. 0.0370 0.0418 0.0385 0 0.0330
sigma^2 estimated as 0.0003265: log likelihood = 1857.48, aic = -3704.96
> tsdiag(m1,gof=20)
> dpus=diff(pus)
> m3=lm(dpgs~-1+dpus)
> summary(m3)
Call:
lm(formula = dpgs ~ -1 + dpus)
Residuals:
Min 1Q Median 3Q Max
-0.076149 -0.008834 0.000365 0.009441 0.151350
Coefficients:
Estimate Std. Error t value Pr(>|t|)
dpus 0.28703 0.01507 19.05 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.01839 on 715 degrees of freedom
Multiple R-squared: 0.3366, Adjusted R-squared: 0.3357
F-statistic: 362.8 on 1 and 715 DF, p-value: < 2.2e-16
> acf(m3$residuals,lag=20)
> pacf(m3$residuals,lag=20)
> m4=ar(m3$residuals,method='mle')
> m4$order
[1] 6
> m4=arima(dpgs,order=c(6,0,0),include.mean=F,xreg=dpus)
> m4
Call:
arima(x = dpgs, order = c(6, 0, 0), xreg = dpus, include.mean = F)
Coefficients:
ar1 ar2 ar3 ar4 ar5 ar6 dpus
0.3953 0.1634 0.0946 0.0297 -0.0873 -0.0525 0.1927
s.e. 0.0389 0.0400 0.0404 0.0405 0.0400 0.0373 0.0136
sigma^2 estimated as 0.0002524: log likelihood = 1949.61, aic = -3883.21
> m4=arima(dpgs,order=c(5,0,0),include.mean=F,xreg=dpus)
> m4
Call:
arima(x = dpgs, order = c(5, 0, 0), xreg = dpus, include.mean = F)
Coefficients:
ar1 ar2 ar3 ar4 ar5 dpus
0.4022 0.1621 0.0899 0.0209 -0.1086 0.1914
s.e. 0.0387 0.0401 0.0403 0.0400 0.0371 0.0136
sigma^2 estimated as 0.0002531: log likelihood = 1948.62, aic = -3883.23
> m4=arima(dpgs,order=c(5,0,0),include.mean=F,xreg=dpus,fixed=c(NA,NA,NA,0,NA,NA))
Warning message:
In arima(dpgs, order = c(5, 0, 0), include.mean = F, xreg = dpus, :
some AR parameters were fixed: setting transform.pars = FALSE
> m4
Call:
arima(x = dpgs, order = c(5, 0, 0), xreg = dpus, include.mean = F, fixed = c(NA,
NA, NA, 0, NA, NA))
Coefficients:
ar1 ar2 ar3 ar4 ar5 dpus
0.4037 0.1642 0.0961 0 -0.1014 0.1911
s.e. 0.0386 0.0399 0.0386 0 0.0345 0.0136
sigma^2 estimated as 0.0002532: log likelihood = 1948.48, aic = -3884.95
> tsdiag(m4,gof=20)
> c1=c(NA,NA,NA,0,NA)
> pm1=backtest(m1,dpgs,316,1,fixed=c1,inc.mean=F)
Error: could not find function "backtest"
> c4=c(NA,NA,NA,0,NA,NA)
> pm4=backtest(m4,dpgs,316,1,xre=dpus,inc.mean=F,fixed=c4)
Error: could not find function "backtest"
> tdx=tdx[2:717]
> pm4fit=dpgs[317:716]-pm4$error
Error: object 'pm4' not found
> pm1fit=dpgs[317:716]-pm1$error
Error: object 'pm1' not found
> plot(tdx[317:716],dpgs[317:716],xlab='year',ylab='growth',type='l')
> points(tdx[317:716],pm1fit,pch='*')
Error in xy.coords(x, y) : object 'pm1fit' not found
> plot(tdx[317:716],dpgs[317:716],xlab='year',ylab='growth',type='l')
> points(tdx[317:716],pm4fit,pch='*')
Error in xy.coords(x, y) : object 'pm4fit' not found
> m6=lm(dpgs[2:716]~-1+dpus[1:715])
> summary(m6)
Call:
lm(formula = dpgs[2:716] ~ -1 + dpus[1:715])
Residuals:
Min 1Q Median 3Q Max
-0.088318 -0.011145 -0.000011 0.011391 0.161679
Coefficients:
Estimate Std. Error t value Pr(>|t|)
dpus[1:715] 0.18560 0.01716 10.81 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.02093 on 714 degrees of freedom
Multiple R-squared: 0.1408, Adjusted R-squared: 0.1395
F-statistic: 117 on 1 and 714 DF, p-value: < 2.2e-16
> acf(m6$residuals,lag=20)
> pacf(m6$residuals,lag=20)
> m7=ar(m6$residuals,method='mle')
> m7$order
[1] 9
> m7=arima(dpgs[2:716],order=c(9,0,0),include.mean=F,xreg=dpus[1:715])
> m7
Call:
arima(x = dpgs[2:716], order = c(9, 0, 0), xreg = dpus[1:715], include.mean = F)
Coefficients:
ar1 ar2 ar3 ar4 ar5 ar6 ar7 ar8
0.4559 0.0888 0.1679 -0.0468 -0.0653 -0.0195 -0.0362 0.0797
s.e. 0.0425 0.0410 0.0423 0.0415 0.0416 0.0414 0.0410 0.0408
ar9 dpus[1:715]
-0.0882 0.0454
s.e. 0.0373 0.0174
sigma^2 estimated as 0.0003204: log likelihood = 1861.55, aic = -3701.1
> m7=arima(dpgs[2:716],order=c(9,0,0),include.mean=F,xreg=dpus[1:715],fixed=c(NA,NA,NA,0,NA,0,0,0,NA,NA))
Warning message:
In arima(dpgs[2:716], order = c(9, 0, 0), include.mean = F, xreg = dpus[1:715], :
some AR parameters were fixed: setting transform.pars = FALSE
> m7
Call:
arima(x = dpgs[2:716], order = c(9, 0, 0), xreg = dpus[1:715], include.mean = F,
fixed = c(NA, NA, NA, 0, NA, 0, 0, 0, NA, NA))
Coefficients:
ar1 ar2 ar3 ar4 ar5 ar6 ar7 ar8 ar9 dpus[1:715]
0.4544 0.0877 0.1415 0 -0.0830 0 0 0 -0.0640 0.0406
s.e. 0.0427 0.0413 0.0393 0 0.0345 0 0 0 0.0318 0.0176
sigma^2 estimated as 0.000323: log likelihood = 1858.7, aic = -3703.4
> tsdiag(m7,gof=20)
> c7=c(NA,NA,NA,0,NA,0,0,0,NA,NA)
> pm7=backtest(m7,dpgs[2:716],315,1,xre=dpus[1:715],inc.mean=F,fixed=c7)
Error: could not find function "backtest"
>
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