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ngreiferngreifer
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Doc updates, prep for submission
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‎R/apm_est.R

+9-9
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@@ -50,20 +50,20 @@
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#'
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#' # Combination of 4 models: 2 time trends, 2 lags
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#' models <- apm_mod(list(crude_rate ~ 1),
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#' lag = 0:1,
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#' time_trend = 0:1)
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#' lag = 0:1,
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#' time_trend = 0:1)
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#' models
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#'
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#' # Fit the models to data; unit_var must be supplied for
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#' # fixed effects
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#' fits <- apm_pre(models,
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#' data = ptpdata,
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#' group_var = "group",
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#' time_var = "year",
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#' val_times = 2004:2007,
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#' unit_var = "state",
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#' nsim = 100,
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#' verbose = FALSE)
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#' data = ptpdata,
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#' group_var = "group",
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#' time_var = "year",
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#' val_times = 2004:2007,
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#' unit_var = "state",
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#' nsim = 100,
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#' verbose = FALSE)
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#'
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#' est <- apm_est(fits,
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#' post_time = 2008,

‎R/apm_mod.R

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@@ -22,16 +22,16 @@
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#' # Combination of 8 models: 1 baseline formulas,
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#' # 2 families, 2 lags, 2 time trends
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#' models1 <- apm_mod(crude_rate ~ 1,
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#' family = list("gaussian", "quasipoisson"),
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#' time_trend = 0:1,
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#' lag = 0:1, fixef = TRUE)
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#' family = list("gaussian", "quasipoisson"),
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#' time_trend = 0:1,
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#' lag = 0:1, fixef = TRUE)
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#' models1
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#'
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#' # Add a single other model with a square time trend
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#' models2 <- apm_mod(crude_rate ~ 1,
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#' family = "gaussian",
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#' time_trend = 2,
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#' fixef = FALSE)
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#' family = "gaussian",
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#' time_trend = 2,
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#' fixef = FALSE)
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#' models2
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#'
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#' (models <- c(models1, models2))

‎R/apm_pre.R

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@@ -36,18 +36,19 @@
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#' # Combination of 8 models: 2 baseline formulas,
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#' # 2 families, 2 lags
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#' models <- apm_mod(crude_rate ~ 1,
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#' family = list("gaussian", "quasipoisson"),
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#' time_trend = 0:1,
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#' lag = 0:1)
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#' family = list("gaussian", "quasipoisson"),
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#' time_trend = 0:1,
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#' lag = 0:1)
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#' models
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#'
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#' # Fit the models to data
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#' fits <- apm_pre(models, data = ptpdata,
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#' group_var = "group",
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#' time_var = "year",
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#' val_times = 1999:2007,
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#' unit_var = "state",
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#' verbose = FALSE)
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#' group_var = "group",
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#' time_var = "year",
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#' val_times = 1999:2007,
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#' unit_var = "state",
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#' nsim = 200,
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#' verbose = FALSE)
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#'
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#' fits
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#'

‎R/plot.apm_pre_fits.R

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@@ -30,20 +30,20 @@
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#' # Combination of 8 models: 2 baseline formulas,
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#' # 2 families, 2 lags
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#' models <- apm_mod(crude_rate ~ 1,
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#' family = "gaussian",
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#' time_trend = 0:1,
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#' lag = 0:1,
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#' diff_k = 0:1)
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#' family = "gaussian",
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#' time_trend = 0:1,
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#' lag = 0:1,
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#' diff_k = 0:1)
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#' models
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#'
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#' # Fit the models to data
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#' fits <- apm_pre(models, data = ptpdata,
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#' group_var = "group",
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#' time_var = "year",
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#' val_times = 1999:2007,
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#' unit_var = "state",
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#' nsim = 50,
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#' verbose = FALSE)
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#' group_var = "group",
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#' time_var = "year",
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#' val_times = 1999:2007,
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#' unit_var = "state",
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#' nsim = 50,
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#' verbose = FALSE)
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#' fits
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#'
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#' plot(fits, type = "weights")

‎R/robustness_bound.R

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#'
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#' # Combination of 4 models: 2 time trends, 2 lags
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#' models <- apm_mod(list(crude_rate ~ 1),
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#' lag = 0:1,
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#' time_trend = 0:1)
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#' lag = 0:1,
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#' time_trend = 0:1)
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#' models
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#'
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#' # Fit the models to data; unit_var must be supplied for
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#' # fixed effects
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#' fits <- apm_pre(models,
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#' data = ptpdata,
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#' group_var = "group",
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#' time_var = "year",
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#' val_times = 2004:2007,
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#' unit_var = "state",
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#' nsim = 100,
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#' verbose = FALSE)
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#' data = ptpdata,
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#' group_var = "group",
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#' time_var = "year",
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#' val_times = 2004:2007,
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#' unit_var = "state",
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#' nsim = 100,
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#' verbose = FALSE)
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#'
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#' est <- apm_est(fits,
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#' post_time = 2008,

‎man/apm-package.Rd

+1-1
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‎man/apm_est.Rd

+9-9
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‎man/apm_mod.Rd

+6-6
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‎man/apm_pre.Rd

+9-8
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‎man/plot.apm_pre_fits.Rd

+10-10
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‎man/robustness_bound.Rd

+9-9
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