datana (version 1.1.2)

rankmod: Function to produce a table ranks the models being analyzed.

Description

Prepare a table that ranks previously fitted models according to a series of statistics

Usage

rankmod(
  tabstatmod = tabstatmod,
  all.refstat = TRUE,
  refstat = refstat,
  want.all.outputs = FALSE
)

Value

The main result is a table having assigned scores for each of the statistics, as well as the sum of the scores. The column ranking has between the best ranking (number 1) to the lowest ranking (number equal to the quantity of models being analyzed). The actual output is a list with two elements: (1) a dataframe sorted by the number of the model, and (2) a dataframe sorted by the ranking of the model.

Arguments

tabstatmod

a data object having the statistics values for each model. The first column must have the name of the model, and the other columns are the statistics.

all.refstat

A logic option to specify the statistics to be used for ranking the models. By default is to TRUE, implying that all the statistics provided in the object (i.e., columns) are going to be used for developing the ranking. If the option all.refstat is set to FALSE, then the option refstat must be specified.

refstat

A vector with the names of the columns (i.e., statistics) to be used. By the default is the name of all the columns of the object tabstatmod but not including the first column (it has the name of the model).

want.all.outputs

A logic option to save a full set of result elements in the output, thus the output is class list. By default is set to FALSE.

Author

Christian Salas-Eljatib and Marcos Marivil.

Details

The function assigns scores to models based on an array of statistics already computed. For instance, the function can use the three prediction capabilities statistics RMSD, AD, and AAD, that are computed by the function valesta(). Nonetheless, any other statistics can be provided to the function. The only requirement is that the lower the value of the statistics (in absolute value), the better. The current version of the function is based upon the approach proposed by Salas (2002).

References

• Salas C. 2002. Ajuste y validación de ecuaciones de volumen para un relicto del bosque de roble-laurel-lingue. Bosque 23(2):81–92. tools:::Rd_expr_doi("10.4067/S0717-92002002000200009").

Examples

##Creates a fake dataframe  
set.seed(1234);y<-rnorm(30, 30,9);x<-rnorm(30, 450,133);z<-rbeta(30, .1,2)
db <- as.data.frame(cbind(y, x,z))
## Fitting some models
mod1 <- lm(y~x, data=db)
mod2 <- lm(y~x+I(x^2), data=db)
mod3 <- lm(y~z+I(x^2), data=db)
## Preparing the format of the input-data for the function
df.m1<-df.m2<-df.m3<-db
df.m1$model<-"mod1";df.m1$y.aju=fitted(mod1)
df.m2$model<-"mod2";df.m2$y.aju=fitted(mod2)
df.m3$model<-"mod3";df.m3$y.aju=fitted(mod3)
df<-rbind(df.m1,df.m2,df.m3)
head(df)
##Assign validation class
df<-assigncl(data=df,variable="y")
table(df$model)
table(df$y.class)
head(df)
##Computes prediction capabilities statistics
df.torank<-valestamod(data=df,y.obs = "y", y.pred="y.aju",
        want.by.valcl = TRUE,val.class = "y.class")
df.torank
##Example 1: getting the main output, sorted by the ranking
rankmod(tabstatmod = df.torank)
##Example 2: only consider a portion of the availables statistics
rankmod(tabstatmod = df.torank, all.refstat=FALSE,
refstat=c("rmsd","ad","aad"))