## Bug #5611

open### LinearModel actor doesn't handle input variables properly

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**Description**

The R code in the RExpression-based LinearModel actor has several problems:

1. In a linear model, it's the *independent* (predictor) variables that can be either numeric or factor (categorical). The dependent (response) variable must be numeric. The actor code gets this reversed, and fails with an error depending on the inputs.

2. The conditional is.character() in the final 'if' statement always evaluates to FALSE because of the conversion-to-factor in the first 'if' statement.

3. The intercept and slope aren't reported out in any useful way, and the intercept isn't even printed to the console output (if displayed).

I'd suggest the following replacement, which doesn't conform exactly to the intended behavior of the original actor, but I think provides a nice starter template for doing a univariate linear model fit. I also changed it to emit the fitted model object itself, which could be passed to another actor for summarizing, generating an ANOVA table, extracting coefficient estimates, etc.

Note that I wouldn't usually explicitly store the model formula as an object, but here I think it's useful to indicate the mapping of input ports to model variables right at the top.

#--------------------------------------------------

model <- Dependent ~ Independent

if (is.character(Independent)) {

Independent <- factor(Independent)

}

- fit model; fitted lm object is available on output port

results <- lm(model)

print(summary(results))

- plot data, adding regression line if appropriate

plot(model)

if (is.numeric(Independent)) {

abline(results, col="red")

}

#--------------------------------------------------