fn_ARSS

The function fn_ARSS perform the Coincident Curves Test, to determine if there are significant differences between the fitted curves for each database.It is based on the Analysis of the Residual Sum of Squares (ARSS) (Chen et al. 1992).

Usage

fn_ARSS(List_TCCT, i, alfa = 0.05)

Arguments

List_TCCT

An empty list to save the matrix results from each regression.

i

An integer value indicating the ith regression analyzed.

alfa

A numerical value that defines the significance level. If this is not set, the default number is 0.05.

Value

List_TCCT calculations for ARSS are stored here

Details

The residual sum of squares (RSS) and the degrees of freedom (DF) for each fitted regression are stored previously in the List_TCCT list. Calculations for ARSS are also stored here.

Inside the function, the RSS and DF for the joined sample are calculated to perform the F test for two tails alpha/2. The decision criteria is performed: "*" if the p-value is less than or equal to alpha or "NS" if the p-value is greater than alpha.

The function requires defining.

See also

FDist from the package stats (version 4.4.0)

Examples

if (FALSE) { # \dontrun{

# The Total length (LT) - Total weight (WT) was estimated for the bullseye puffer
# *Sphoeroides annulatus* for landed categories: Fresh, Frozen-thawed (Frozen), Total
# (All sample) and Joined (sum of values of Fresh and Frozen). The Residual Sum of
# Squares (RSS) and the degrees of freedom (DF) are provided for each data source.
# In the table the first row displays the Analysis of Residual Sum of Squares (ARSS),
# the p-value (p), and the decision criteria for the ARSS test (Criteria).

# The adjusted models show the following data: Fresh SSR=   and DF= 742; Frozen
# SSR= 1280131.81 and DF= 651; and the total sample SSR= 6115874.53 and DF= 1395.
# Values are stored in the table `Table_CC`, this is stored in a list, and the name
# of each item is built with the acronyms of the model variables (e.g. LTWT).

Table_CC <- data.frame(matrix(NA,nrow=4,ncol=8))
Table_CC[1,1] <- "Lt-WT"
Table_CC[,2] <- c("Fresh","Frozen","Total","Joined")
colnames(Table_CC) <- c("Model","Category","RSS","DF","ARSS","F-table","p-value","Criteria")

Table_CC[1,3] <- 4424418.33
Table_CC[1,4] <-  742
Table_CC[2,3] <- 1280131.81
Table_CC[2,4] <-  651
Table_CC[3,3] <- 6115874.53
Table_CC[3,4] <-  1395

List_ARSS <- list(LTWT=Table_CC)

i <- 1

ARSS <- fn_ARSS(List_ARSS, i,  alfa= 0.05)
ARSS[[i]]
} # }