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prdm0 merged 1 commit into from
Aug 3, 2026
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version 0.1.1.9000 #5

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4 changes: 2 additions & 2 deletions R/data.R
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Original file line number Diff line number Diff line change
Expand Up @@ -121,7 +121,7 @@
#' data(Crime2009)
#' Crime2009[Crime2009$state == "Alabama", ]
#'
#' fit <- lm(violent ~ poverty + single, data = Crime2009)
#' fit <- lm(murder ~ hs_grad + poverty + single, data = Crime2009)
#' hcinfer(fit, type = "hcbeta")
#'
"Crime2009"
Expand Down Expand Up @@ -157,7 +157,7 @@
#' data(Hprice)
#' head(Hprice)
#'
#' fit <- lm(price ~ lotsize + sqrft + bdrms, data = Hprice)
#' fit <- lm(price ~ lotsize + bdrms + bdrms:sqrft, data = Hprice)
#' hcinfer(fit, type = "hcbeta")
#'
"Hprice"
2 changes: 1 addition & 1 deletion man/Crime2009.Rd
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2 changes: 1 addition & 1 deletion man/Hprice.Rd
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8 changes: 5 additions & 3 deletions vignettes/hcinfer-comparison.Rmd
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Expand Up @@ -23,13 +23,15 @@ diagnostics.

## Fit one model

Comparisons should start from one fitted model. Here we use a house-price
regression and focus on the lot-size coefficient.
Comparisons should start from one fitted model. Here we use the Boston
house-price model from the HCbeta paper (price regressed on lot size, number of
bedrooms, and a bedrooms-by-size interaction) and focus on the lot-size
coefficient.

```{r}
library(hcinfer)

fit <- lm(price ~ lotsize + sqrft + bdrms, data = Hprice)
fit <- lm(price ~ lotsize + bdrms + bdrms:sqrft, data = Hprice)
```

## Run several methods
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12 changes: 7 additions & 5 deletions vignettes/hcinfer-hcbeta.Rmd
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Expand Up @@ -16,10 +16,12 @@ knitr::opts_chunk$set(
options(hcinfer.use_emoji = FALSE)
```

This vignette shows how to run HCbeta on the Crime2009 dataset, inspect its
method parameters and diagnostic quantities, and run a small sensitivity check
on its tuning controls. It assumes the introduction (`vignette("introduction",
package = "hcinfer")`).
This vignette shows how to run HCbeta on the `Crime2009` dataset, the 2009 U.S.
crime application from the HCbeta paper, which regresses the murder rate on
high-school graduation, poverty, and single-parent household rates. It inspects
HCbeta's method parameters and diagnostic quantities, and runs a small
sensitivity check on its tuning controls. It assumes the introduction
(`vignette("introduction", package = "hcinfer")`).

## Run HCbeta

Expand All @@ -29,7 +31,7 @@ default `hcinfer(fit)` call.
```{r run-hcbeta}
library(hcinfer)

fit <- lm(violent ~ hs_grad + poverty + single, data = Crime2009)
fit <- lm(murder ~ hs_grad + poverty + single, data = Crime2009)
result <- hcinfer(fit, type = "hcbeta")

summary(result)
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