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use styler #23

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Feb 10, 2018
Merged

use styler #23

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5 changes: 2 additions & 3 deletions R/RcppExports.R
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Original file line number Diff line number Diff line change
Expand Up @@ -2,10 +2,9 @@
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

nsignC <- function(x) {
.Call(`_inferr_nsignC`, x)
.Call(`_inferr_nsignC`, x)
}

gvar <- function(ln, ly) {
.Call(`_inferr_gvar`, ln, ly)
.Call(`_inferr_gvar`, ln, ly)
}

34 changes: 16 additions & 18 deletions R/infer-anova.R
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Expand Up @@ -36,45 +36,43 @@
#' infer_oneway_anova(hsb, write, prog)
#' @export
#'
infer_oneway_anova <- function(data, x, y, ...) UseMethod('infer_oneway_anova')
infer_oneway_anova <- function(data, x, y, ...) UseMethod("infer_oneway_anova")

#' @export
infer_oneway_anova.default <- function(data, x, y, ...) {

x1 <- enquo(x)
y1 <- enquo(y)

fdata <-
data %>%
select(!! x1, !! y1)
data %>%
select(!! x1, !! y1)

sample_mean <- anova_avg(fdata, !! x1)
sample_stats <- anova_split(fdata, !! x1, !! y1, sample_mean)
k <- anova_calc(fdata, sample_stats, !! x1, !! y1)


result <- list(between = k$sstr, within = k$ssee, total = k$total,
df_btw = k$df_sstr, df_within = k$df_sse,
df_total = k$df_sst, ms_btw = k$mstr, ms_within = k$mse,
f = k$f, p = k$sig, r2 = round(k$reg$r.squared, 4),
ar2 = round(k$reg$adj.r.squared, 4),
sigma = round(k$reg$sigma, 4), obs = k$obs,
tab = sample_stats[, c(1, 2, 3, 5)])

class(result) <- 'infer_oneway_anova'
return(result)
result <- list(
between = k$sstr, within = k$ssee, total = k$total,
df_btw = k$df_sstr, df_within = k$df_sse,
df_total = k$df_sst, ms_btw = k$mstr, ms_within = k$mse,
f = k$f, p = k$sig, r2 = round(k$reg$r.squared, 4),
ar2 = round(k$reg$adj.r.squared, 4),
sigma = round(k$reg$sigma, 4), obs = k$obs,
tab = sample_stats[, c(1, 2, 3, 5)]
)

class(result) <- "infer_oneway_anova"
return(result)
}

#' @export
#' @rdname infer_oneway_anova
#' @usage NULL
#'
owanova <- function(data, x, y, ...) {

.Deprecated("infer_oneway_anova()")
infer_oneway_anova(data, x, y, ...)

.Deprecated("infer_oneway_anova()")
infer_oneway_anova(data, x, y, ...)
}

#' @export
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89 changes: 42 additions & 47 deletions R/infer-binom-test.R
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Expand Up @@ -34,45 +34,44 @@
#' infer_binom_test(hsb, female, prob = 0.5)
#' @export
#'
infer_binom_calc <- function(n, success, prob = 0.5, ...) UseMethod('infer_binom_calc')
infer_binom_calc <- function(n, success, prob = 0.5, ...) UseMethod("infer_binom_calc")

#' @export
infer_binom_calc.default <- function(n, success, prob = 0.5, ...) {
if (!is.numeric(n)) {
stop("n must be an integer")
}

if (!is.numeric(n)) {
stop('n must be an integer')
}
if (!is.numeric(success)) {
stop("success must be an integer")
}

if (!is.numeric(success)) {
stop('success must be an integer')
}
if (!is.numeric(prob)) {
stop("prob must be numeric")
}

if(!is.numeric(prob)) {
stop('prob must be numeric')
}
if ((prob < 0) | (prob > 1)) {
stop("prob must be between 0 and 1")
}

if((prob < 0) | (prob > 1)) {
stop('prob must be between 0 and 1')
}
k <- binom_comp(n, success, prob)

k <- binom_comp(n, success, prob)
out <- list(
n = n, k = k$k, exp_k = k$exp_k, obs_p = k$obs_p,
exp_p = k$exp_p, lower = k$lower, upper = k$upper
)

out <- list(n = n, k = k$k, exp_k = k$exp_k, obs_p = k$obs_p,
exp_p = k$exp_p, lower = k$lower, upper = k$upper)

class(out) <- 'infer_binom_calc'
return(out)
class(out) <- "infer_binom_calc"
return(out)
}

#' @export
#' @rdname infer_binom_calc
#' @usage NULL
#'
binom_calc <- function(n, success, prob = 0.5, ...) {

.Deprecated("infer_binom_calc()")
infer_binom_calc(n, success, prob = 0.5, ...)

.Deprecated("infer_binom_calc()")
infer_binom_calc(n, success, prob = 0.5, ...)
}

#' @export
Expand All @@ -83,41 +82,37 @@ print.infer_binom_calc <- function(x, ...) {
#' @export
#' @rdname infer_binom_calc
infer_binom_test <- function(data, variable, prob = 0.5) {
varyable <- enquo(variable)

varyable <- enquo(variable)

fdata <-
data %>%
pull(!! varyable)
fdata <-
data %>%
pull(!! varyable)

if (!is.factor(fdata)) {
stop('variable must be of type factor', call. = FALSE)
}
if (!is.factor(fdata)) {
stop("variable must be of type factor", call. = FALSE)
}

if (nlevels(fdata) > 2) {
stop('Binomial test is applicable only to binary data i.e. categorical data with 2 levels.', call. = FALSE)
}
if (nlevels(fdata) > 2) {
stop("Binomial test is applicable only to binary data i.e. categorical data with 2 levels.", call. = FALSE)
}

if(!is.numeric(prob)) {
stop('prob must be numeric', call. = FALSE)
}
if (!is.numeric(prob)) {
stop("prob must be numeric", call. = FALSE)
}

if((prob < 0) | (prob > 1)) {
stop('prob must be between 0 and 1', call. = FALSE)
}
if ((prob < 0) | (prob > 1)) {
stop("prob must be between 0 and 1", call. = FALSE)
}

n <- length(fdata)
k <- table(fdata)[[2]]
infer_binom_calc.default(n, k, prob)
n <- length(fdata)
k <- table(fdata)[[2]]
infer_binom_calc.default(n, k, prob)
}

#' @export
#' @rdname infer_binom_calc
#' @usage NULL
#'
binom_test <- function(data, prob = 0.5) {

.Deprecated("infer_binom_test()")


.Deprecated("infer_binom_test()")
}
129 changes: 62 additions & 67 deletions R/infer-chisq-assoc-test.R
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Expand Up @@ -37,83 +37,78 @@
#' infer_chisq_assoc_test(hsb, female, ses)
#' @export
#'
infer_chisq_assoc_test <- function(data, x, y) UseMethod('infer_chisq_assoc_test')
infer_chisq_assoc_test <- function(data, x, y) UseMethod("infer_chisq_assoc_test")

#' @export
infer_chisq_assoc_test.default <- function(data, x, y) {

x1 <- enquo(x)
y1 <- enquo(y)

xone <-
data %>%
pull(!! x1)

yone <-
data %>%
pull(!! y1)

if (!is.factor(xone)) {
stop('x must be a categorical variable')
}

if (!is.factor(yone)) {
stop('y must be a categorical variable')
}

# dimensions
k <- table(xone, yone)
dk <- dim(k)
ds <- prod(dk)
nr <- dk[1]
nc <- dk[2]


if (ds == 4) {

twoway <- matrix(table(xone, yone), nrow = 2)
df <- df_chi(twoway)
ef <- efmat(twoway)
k <- pear_chsq(twoway, df, ef)
m <- lr_chsq(twoway, df, ef)
n <- yates_chsq(twoway)
p <- mh_chsq(twoway, n$total, n$prod_totals)

} else {

twoway <- matrix(table(xone, yone), nrow = dk[1])
ef <- efm(twoway, dk)
df <- df_chi(twoway)
k <- pear_chi(twoway, df, ef)
m <- lr_chsq2(twoway, df, ef, ds)

}

j <- chigf(xone, yone, k$chi)

result <- if (ds == 4) {
list(chi = k$chi, chilr = m$chilr, chimh = p$chimh, chiy = n$chi_y,
sig = k$sig, siglr = m$sig_lr, sigy = n$sig_y, sigmh = p$sig_mh,
phi = j$phi, cc = j$cc, cv = j$cv, ds = ds, df = df)
} else {
list(df = df, chi = k$chi, chilr = m$chilr, sig = k$sig, siglr = m$sig_lr,
phi = j$phi, cc = j$cc, cv = j$cv, ds = ds)
}

class(result) <- 'infer_chisq_assoc_test'
return(result)

x1 <- enquo(x)
y1 <- enquo(y)

xone <-
data %>%
pull(!! x1)

yone <-
data %>%
pull(!! y1)

if (!is.factor(xone)) {
stop("x must be a categorical variable")
}

if (!is.factor(yone)) {
stop("y must be a categorical variable")
}

# dimensions
k <- table(xone, yone)
dk <- dim(k)
ds <- prod(dk)
nr <- dk[1]
nc <- dk[2]


if (ds == 4) {
twoway <- matrix(table(xone, yone), nrow = 2)
df <- df_chi(twoway)
ef <- efmat(twoway)
k <- pear_chsq(twoway, df, ef)
m <- lr_chsq(twoway, df, ef)
n <- yates_chsq(twoway)
p <- mh_chsq(twoway, n$total, n$prod_totals)
} else {
twoway <- matrix(table(xone, yone), nrow = dk[1])
ef <- efm(twoway, dk)
df <- df_chi(twoway)
k <- pear_chi(twoway, df, ef)
m <- lr_chsq2(twoway, df, ef, ds)
}

j <- chigf(xone, yone, k$chi)

result <- if (ds == 4) {
list(
chi = k$chi, chilr = m$chilr, chimh = p$chimh, chiy = n$chi_y,
sig = k$sig, siglr = m$sig_lr, sigy = n$sig_y, sigmh = p$sig_mh,
phi = j$phi, cc = j$cc, cv = j$cv, ds = ds, df = df
)
} else {
list(
df = df, chi = k$chi, chilr = m$chilr, sig = k$sig, siglr = m$sig_lr,
phi = j$phi, cc = j$cc, cv = j$cv, ds = ds
)
}

class(result) <- "infer_chisq_assoc_test"
return(result)
}

#' @export
#' @rdname infer_chisq_assoc_test
#' @usage NULL
#'
chisq_test <- function(x, y) {

.Deprecated("infer_chisq_assoc_test()")


.Deprecated("infer_chisq_assoc_test()")
}

#' @export
Expand Down
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