rice {ipsRdbs}

Riece yield data

Description

Riece yield data

Usage

rice

Format

A data frame with three columns and 68 rows:

Yield

Yield of rice in kilograms

Days

Number of days after flowering before harvesting

Source

Bal and Ojha (1975).

Examples

 summary(rice)
 plot(rice$Days, rice$Yield, pch="*", xlab="Days", ylab="Yield")
 rice$daymin31 <- rice$Days-31
 rice.lm <- lm(Yield ~ daymin31, data=rice)
 summary(rice.lm)
 # Check the diagnostics 
 plot(rice.lm$fit, rice.lm$res, xlab="Fitted values", ylab = "Residuals")
 abline(h=0)
 # Should be a random scatter
 # Needs a quadratic term
 
 qqnorm(rice.lm$res, col=2)
 qqline(rice.lm$res, col="blue")
 rice.lm2 <- lm(Yield ~ daymin31 + I(daymin31^2) , data=rice)
 old.par <- par(no.readonly = TRUE)
 par(mfrow=c(1, 2))
 plot(rice.lm2$fit, rice.lm2$res, xlab="Fitted values", ylab = "Residuals")
 abline(h=0)
 # Should be a random scatter 
 # Much better plot!
 qqnorm(rice.lm2$res, col=2)
 qqline(rice.lm2$res, col="blue")
 summary(rice.lm2)
 par(old.par) # par(mfrow=c(1,1))
 plot(rice$Days,  rice$Yield, xlab="Days", ylab="Yield")
 lines(rice$Days, rice.lm2$fit, lty=1, col=3)
 rice.lm3 <- lm(Yield ~ daymin31 + I(daymin31^2)+I(daymin31^3) , data=rice)
 #check the diagnostics 
 summary(rice.lm3) # Will print the summary of the fitted model 
 #### Predict at a new value of Days=31.1465
 
 # Create a new data set called new
 new <- data.frame(daymin31=32.1465-31)
 
 a <- predict(rice.lm2, newdata=new, se.fit=TRUE) 
 # Confidence interval for the mean of rice yield  at day=31.1465
 a <- predict(rice.lm2, newdata=new, interval="confidence") 
 a
 #          fit      lwr      upr
 # [1,] 3676.766 3511.904 3841.628
 # Prediction interval for a future yield at day=31.1465
 b <- predict(rice.lm2, newdata=new, interval="prediction") 
 b
 # fit      lwr      upr
 #[1,] 3676.766 3206.461 4147.071