What are the key components and functions for standard model objects in R?

Question

I have implemented a new statistical model in R and it works in my sandbox, but I would like to make it more standard. A good comparison is lm(), where I can t

Answer 1

The following code:

library(hints)
hints(class="lm")

will provide all Functions for lm as:

Functions for lm in package ‘base’:

kappa                   Compute or Estimate the Condition Number of a
                        Matrix
base-defunct            Defunct Functions in Package 'base'
rcond                   Compute or Estimate the Condition Number of a
                        Matrix

Functions for lm in package ‘gam’:

deviance.lm             Service functions and as yet undocumented
                        functions for the gam library

Functions for lm in package ‘gdata’:

nobs                    Compute the Number of Non-missing Observations

Functions for lm in package ‘methods’:

setOldClass             Register Old-Style (S3) Classes and Inheritance

Functions for lm in package ‘stats’:

add1                    Add or Drop All Possible Single Terms to a
                        Model
alias                   Find Aliases (Dependencies) in a Model
anova.lm                ANOVA for Linear Model Fits
case.names.lm           Case and Variable Names of Fitted Models
cooks.distance.lm       Regression Deletion Diagnostics
dfbeta.lm               Regression Deletion Diagnostics
dfbetas.lm              Regression Deletion Diagnostics
drop1.lm                Add or Drop All Possible Single Terms to a
                        Model
dummy.coef.lm           Extract Coefficients in Original Coding
effects                 Effects from Fitted Model
family.lm               Accessing Linear Model Fits
formula.lm              Accessing Linear Model Fits
hatvalues.lm            Regression Deletion Diagnostics
influence.lm            Regression Diagnostics
labels.lm               Accessing Linear Model Fits
logLik                  Extract Log-Likelihood
model.frame.lm          Extracting the Model Frame from a Formula or
                        Fit
model.matrix.lm         Construct Design Matrices
plot.lm                 Plot Diagnostics for an lm Object
print.lm                Fitting Linear Models
proj                    Projections of Models
residuals.lm            Accessing Linear Model Fits
rstandard.lm            Regression Deletion Diagnostics
rstudent.lm             Regression Deletion Diagnostics
summary.lm              Summarizing Linear Model Fits
variable.names.lm       Case and Variable Names of Fitted Models
vcov                    Calculate Variance-Covariance Matrix for a
                        Fitted Model Object
case.names              Case and Variable Names of Fitted Models
dummy.coef              Extract Coefficients in Original Coding
influence.measures      Regression Deletion Diagnostics
lm.influence            Regression Diagnostics
lm                      Fitting Linear Models
lm.fit                  Fitter Functions for Linear Models
model.frame             Extracting the Model Frame from a Formula or
                        Fit
model.matrix            Construct Design Matrices
stats-defunct           Defunct Functions in Package 'stats'
lm.glm                  Some linear and generalized linear modelling
                        examples from `An Introduction to Statistical
                        Modelling' by Annette Dobson

Functions for lm in package ‘unknown’:

confint.lm              NA
extractAIC.lm           NA
qr.lm                   NA
simulate.lm             NA

Functions for lm in package ‘VGAM’:

predict.lm              Undocumented and Internally Used Functions and
                        Classes

Functions for lm in package ‘xtable’:

xtable                  Create Export Tables