Displaying 1 result from an estimated 1 matches for "penscale".
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parscale
2012 Jan 10
1
grplasso
...my groups and run the lasso regression?
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Looks like this is the grouping part:
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index<-c(NA,)
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but I'm not sure how to specify the df for the variables past the NA for the intercept.
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Once that's defined the penalty can be specified:
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lambda <- lambdamax(x, y = y, index = index, penscale = sqrt,
model = LogReg()) * 0.5^(0:5)?
In my case I'd use LinReg for the model.?
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Then the model:
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fit <- grplasso(x, y = y, index = index, lambda = lambda, model = LogReg(),
penscale = sqrt, control = grpl.control(update.hess = "lambda", trace = 0))
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again using LinReg for the...