autocorrelation class exercise

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co2 <- read.csv(file.choose(), header = TRUE)

## Error: file choice cancelled

head(co2)

## [1] 315.4 316.3 316.5 317.6 318.1 318.0

sitexlm <- lm(co2 ~ time + I(time^2), data = co2)

## Error: non-numeric argument to binary operator

mloa.ts <- ts(co2$co2, start = min(co2$year), frequency = 12)

## Error: $ operator is invalid for atomic vectors

plot(decompose(mloa.ts))

## Error: object 'mloa.ts' not found

season <- cycle(mloa.ts)

## Error: object 'mloa.ts' not found

season

## Error: object 'season' not found

mllm <- lm(co2$co2 ~ co2$time)

## Error: $ operator is invalid for atomic vectors

acf(resid(mllm))$acf[2]

## Error: object 'mllm' not found

library(lmtest)

## Loading required package: zoo

## Attaching package: 'zoo'

## The following object(s) are masked from 'package:base':
## 
## as.Date, as.Date.numeric

dwtest(mllm)

## Error: object 'mllm' not found

library(orcutt)

cochrane.orcutt(lm(co2$co2 ~ co2$time))$rho

## Error: $ operator is invalid for atomic vectors

plot(sitexlm)

## Error: object 'sitexlm' not found

lmx <- lm(co2$co2 ~ co2$time + factor(season))

## Error: $ operator is invalid for atomic vectors

ts.plot(cbind(mloa.ts, lmx$fitted), lty = 1:2, col = c(1, 2))

## Error: object 'mloa.ts' not found

# mlnlm<-gls(co2~time, data=co2, cor=corAR1(0.839)) does not recognize
# function 'gls' confint(mlnlm)

You can also embed plots, for example:

plot(decompose(mloa.ts))

## Error: object 'mloa.ts' not found