View source: R/helper_estimators_weights.R
checkConvergence | R Documentation |
Check convergence of an algorithm using one of the following criteria:
diff_absolute
Checks if the largest elementwise absolute difference
between two matrices .W_new
and W.old
is
smaller than a given tolerance.
diff_squared
Checks if the largest elementwise squared difference
between two matrices .W_new
and W.old
is
smaller than a given tolerance.
diff_relative
Checks if the largest elementwise absolute rate of change
(new - old / new) for two matrices .W_new
and W.old
is smaller than a given tolerance.
checkConvergence( .W_new = args_default()$.W_new, .W_old = args_default()$.W_old, .conv_criterion = args_default()$.conv_criterion, .tolerance = args_default()$.tolerance )
.W_new |
A (J x K) matrix of weights. |
.W_old |
A (J x K) matrix of weights. |
.conv_criterion |
Character string. The criterion to use for the convergence check. One of: "diff_absolute", "diff_squared", or "diff_relative". Defaults to "diff_absolute". |
.tolerance |
Double. The tolerance criterion for convergence.
Defaults to |
TRUE
if converged; FALSE
otherwise.
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