Hi!

I am working on a project where I'm trying to create my own package, mylm, which is meant to replicate most of the functionality that the standard lm() objects in R have. This works fine, both when testing in the R file in my project, but also in a RMarkdown file, where I use chunks to present what the different functions can do. The rmd files are also where the problems arise, when I try to knit the document. In a regular R session it works fine to just use print(mylm_model) or summary(mylm_model), but whenever I knit it seems to use some standard R function for the summary, instead of my self-written one.

However, the knitting works fine when I use summary.mylm(mylm-model), and this might have to be my emergency solution if I don't figure this out within the next couple of days. Any help is highly appreciated!

The structure of the R file in the package looks like this:

```
# Select Build, Build and reload to build and lode into the R-session.
mylm <- function(formula, data = list(), contrasts = NULL, ...){
# Extract model matrix & responses
mf <- model.frame(formula = formula, data = data)
X <- model.matrix(attr(mf, "terms"), data = mf, contrasts.arg = contrasts)
y <- model.response(mf)
terms <- attr(mf, "terms")
# Add code here to calculate coefficients, residuals, fitted values, etc...
# and store the results in the list est
est <- list(terms = terms, model = mf)
# Store call and formula used
est$call <- match.call()
est$formula <- formula
# Set class name. This is very important!
class(est) <- 'mylm'
# Return the object with all results
return(est)
}
print.mylm <- function(object, ...){
# Code here is used when print(object) is used on objects of class "mylm"
# Useful functions include cat, print.default and format
cat('Info about object\n')
}
summary.mylm <- function(object, ...){
# Code here is used when summary(object) is used on objects of class "mylm"
# Useful functions include cat, print.default and format
cat('Summary of object\n')
}
plot.mylm <- function(object, ...){
# Code here is used when plot(object) is used on objects of class "mylm"
}
# This part is optional! You do not have to implement anova
anova.mylm <- function(object, ...){
# Code here is used when anova(object) is used on objects of class "mylm"
# Components to test
comp <- attr(object$terms, "term.labels")
# Name of response
response <- deparse(object$terms[[2]])
# Fit the sequence of models
txtFormula <- paste(response, "~", sep = "")
model <- list()
for(numComp in 1:length(comp)){
if(numComp == 1){
txtFormula <- paste(txtFormula, comp[numComp])
}
else{
txtFormula <- paste(txtFormula, comp[numComp], sep = "+")
}
formula <- formula(txtFormula)
model[[numComp]] <- lm(formula = formula, data = object$model)
}
# Print Analysis of Variance Table
cat('Analysis of Variance Table\n')
cat(c('Response: ', response, '\n'), sep = '')
cat(' Df Sum sq X2 value Pr(>X2)\n')
for(numComp in 1:length(comp)){
# Add code to print the line for each model tested
}
return(model)
}```
With some added code here and there, within the functions, to actually calculate/return the things I need.
```