Adjusted R^2; 0 for a model with nothing beyond the intercept, as in R.
Whether this is an aov fit.
The term of each coefficient (0 for the intercept).
Coefficients (intercept first); NaN for aliased columns.
Names of the coefficients (the model matrix's column names).
The coefficient table of the columns that are not aliased, in their order.
Estimates (R's Estimate).
Two-sided p-values (R's Pr(>|t|)).
Standard errors (R's Std. Error).
t statistics (R's t value).
Residual degrees of freedom, n - rank (n counts the rows of non-zero weight).
The effects Q'y of the (weighted) fit, one per row of non-zero weight.
R's factors attribute of the terms (one array per variable, one code per term).
Fitted values, one per residual (R's fitted.values).
The formula.
Optionalfp-value of the overall F test; absent with fStatistic.
OptionalfOverall F statistic with its degrees of freedom. Absent (as is fPValue) when the model has nothing beyond the
intercept, where R's summary(lm) has no fstatistic.
Denominator degrees of freedom (the residual degrees of freedom).
Numerator degrees of freedom (rank minus the intercept).
The F statistic.
Whether the model has an intercept.
Number of rows of non-zero weight.
Degree of each term.
The QR decomposition of the (weighted) model matrix.
Numerical rank of the model matrix.
Residuals y - fitted (rows with a missing value dropped; rows of weight 0 included).
The response's name.
0-based indices of the rows of data used.
R^2; 0 for a model with nothing beyond the intercept, as in R.
The weighted residual sum of squares.
Residual standard error.
Labels of the terms.
The variables of the formula, the response first.
R's warnings (from the model matrix and from summary()).
OptionalweightsThe weights (rows used), if any.
The model matrix (rows used).
The response (rows used).
Result of lm with a formula: the fit of the model matrix, with the formula's terms.