A typical medium sized environmental data set with hourly measurements
NOx pollution content in the ambient air.
A data frame with 8088 observations on the following 4 variables.
day number, a factor with levels
730, typically with 24 hourly measurements.
\log of hourly mean of NOx concentration in
ambient air [ppb] next to a highly frequented motorway.
\log of hourly sum of NOx emission of
cars on this motorway in arbitrary units.
Square root of wind speed [m/s].
The original data set had more observations, but with missing values.
Here, all cases with missing values were omitted
na.omit(.)), and then only those were retained that
belonged to days with at least 20 (fully) observed hourly
René Locher (at ZHAW, Switzerland).
another NOx dataset,
data(NOxEmissions) plot(LNOx ~ LNOxEm, data = NOxEmissions, cex = 0.25, col = "gray30") ## Not run: ## these take too much time -- ## p = 340 ==> already Least Squares is not fast (lmNOx <- lm(LNOx ~ . ,data = NOxEmissions)) plot(lmNOx) #-> indication of 1 outlier M.NOx <- MASS::rlm(LNOx ~ . , data = NOxEmissions) ## M-estimation works ## whereas MM-estimation fails: try(MM.NOx <- MASS::rlm(LNOx ~ . , data = NOxEmissions, method = "MM")) ## namely because S-estimation fails: try(lts.NOx <- ltsReg(LNOx ~ . , data = NOxEmissions)) try(lmR.NOx <- lmrob (LNOx ~ . , data = NOxEmissions)) ## End(Not run)