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https://github.com/dwinkler1/fran.git
synced 2026-02-19 22:50:59 -05:00
Daniel Winkler
a5b3147342
It seems to work best when installed directly from nvim with R.nvim loaded. The package asks to install it when it is not present. I set a local `.Rlibs` folder to install into via the `R_LIBS_USER` environment variable. This needs to be deleted when R is updated or leads to a segfault when using nix due to wrong permissions.
52 lines
1.8 KiB
R
52 lines
1.8 KiB
R
cat("Testing\n")
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cat("\n============================================================ fwildclusterboot ============================================================\n")
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library(fwildclusterboot)
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data(voters)
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lm_fit <- lm(
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proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration ,
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data = voters
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)
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boot_lm <- boottest(
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lm_fit,
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clustid = "group_id1",
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param = "treatment",
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B = 999
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)
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boot_lmjl <- boottest(
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lm_fit,
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clustid = "group_id1",
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param = "treatment",
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B = 999#,
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# engine = "WildBootTests.jl"
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)
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#setBoottest_engine("WildBootTests.jl")
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boot_lmjl2 <- boottest(
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lm_fit,
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clustid = "group_id1",
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param = "treatment",
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B = 999
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)
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summary(boot_lm)
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summary(boot_lmjl)
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summary(boot_lmjl2)
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cat("\n============================================================ httpgd ============================================================\n")
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library(httpgd)
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hgd()
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cat("\n============================================================ musicMetadata ============================================================\n")
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library(musicMetadata)
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print(classify_labels('Interscope'))
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cat("\n============================================================ summclust ============================================================\n")
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library(summclust)
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summclust(lm_fit, cluster = ~group_id1, params = "treatment")
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cat("\n============================================================ synthdid ============================================================\n")
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library(synthdid)
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data('california_prop99')
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setup = panel.matrices(california_prop99)
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tau.hat = synthdid_estimate(setup$Y, setup$N0, setup$T0)
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se = sqrt(vcov(tau.hat, method='placebo'))
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sprintf('95%% CI (%1.2f, %1.2f)', tau.hat - 1.96 * se, tau.hat + 1.96 * se)
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cat("\n============================================================ END ============================================================\n")
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