time series - How to make Dummies with R -

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i'm trying forecast daily electricity market price, dataset of 3 years before of daily prices, , want correct seasonal effect because cannot predict prices, want dummy diferentiate everyday of week, everymonday, everytuesday , on.

can explain me how make dummies in r in order diferentiate days on week? dataset daily price, dates. thank much.

you don't have that, in r, can use as.factor() treat variable categorical:

set.seed(784) week <- sample(1:7, 50, rep=t) y    <- rnorm(50)  # treat week factor: m1 <- lm(y ~ as.factor(week)) summary(m1)

results:

coefficients:                  estimate std. error t value pr(>|t|) (intercept)        0.3148     0.3417   0.921    0.362 as.factor(week)2   0.2059     0.5029   0.410    0.684 as.factor(week)3   0.3623     0.5293   0.684    0.497 as.factor(week)4  -0.1308     0.4678  -0.280    0.781 as.factor(week)5   0.6916     0.4678   1.478    0.147 as.factor(week)6  -0.3285     0.4832  -0.680    0.500 as.factor(week)7  -0.6165     0.4555  -1.353    0.183

however, if insist, can use command make dummies:

# manually make dummies: sun <- (week==1) mon <- (week==2) tue <- (week==3) wed <- (week==4) thu <- (week==5) fri <- (week==6) sat <- (week==7)  m2 <- lm(y ~ mon + tue + wed + thu + fri + sat) summary(m2)

the results same:

coefficients:             estimate std. error t value pr(>|t|) (intercept)   0.3148     0.3417   0.921    0.362 montrue       0.2059     0.5029   0.410    0.684 tuetrue       0.3623     0.5293   0.684    0.497 wedtrue      -0.1308     0.4678  -0.280    0.781 thutrue       0.6916     0.4678   1.478    0.147 fritrue      -0.3285     0.4832  -0.680    0.500 sattrue      -0.6165     0.4555  -1.353    0.183

you may want check how treat dates in r, instance, can extract day of week using weekdays():

x <- as.date('3/20/2014',format='%m/%d/%y') weekdays(x)

results:

"thursday"

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