S3 method for class 'sars'. summary.sars creates summary
statistics for objects of class 'sars'. The exact summary statistics
computed depends on the 'Type' attribute (e.g. 'multi') of the 'sars'
object. The summary method generates more useful information for the user
than the standard model fitting functions. Another S3 method
(print.summary.sars; not documented) is used to print the output.
# S3 method for sars
summary(object, ...)An object of class 'sars'.
Further arguments.
The summary.sars function returns an object of class
"summary.sars". A print function is used to obtain and print a summary of
the model fit results.
For a 'sars' object of Type 'fit', a list with 16 elements is returned that contains useful information from the model fit, including the model parameter table (with t-values, p-values and confidence intervals), model fit statistics (e.g. R2, AIC), the observed shape of the model and whether or not the fit is asymptotic, and the results of any additional model checks undertaken (e.g. normality of the residuals).
For a 'sars' object of Type 'multi', a list with 4 elements is returned:
(i) a vector of the names of the models that were successfully fitted and
passed any additional checks, (ii) a character string containing the name
of the criterion used to rank models, (iii) a data frame of the ranked
models, and (iv) a vector of the names of any models that were not fitted
or did not pass any additional checks. In regards to (iii;
Model_table), the dataframe contains the fit summaries for each
successfully fitted model (including the value of the model criterion used
to compare models, the R2 and adjusted R2, and the observed shape of the
fit); the models are ranked in decreasing order of information criterion
weight.
For a 'sars' object of Type 'lin_pow', a list with 5 elements is returned:
(i) the model fit output from the lm function, (ii) the
fitted values of the model, (iii) the observed data, and (iv and v) the
results of the residuals normality and heterogeneity tests. If the argument
compare = TRUE is used in lin_pow, a sixth element is
returned that contains the parameter values from the non-linear power
model.
# NOT RUN {
data(galap)
#fit a multimodel SAR and get the model table
mf <- sar_multi(galap)
summary(mf)
summary(mf)$Model_table
#Get a summary of the fit of the linear power model
fit <- lin_pow(galap, con = 1, compare = TRUE)
summary(fit)
# }
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