2026_mcm_b/latex/.Rhistory

df = tibble(
a = c(1,4,3,7),
b = a + rnorm(4)
)
df
df %>%
pivot_longer(1:2, names_to = "var", values_to = "val")
df %>%
pivot_longer(1:2, names_to = "var", values_to = "val") %>%
ggplot(aes(y = val, color = var)) +
geom_point()
df %>%
pivot_longer(1:2, names_to = "var", values_to = "val") %>%
ggplot(aes(x = 1:4, y = val, color = var)) +
geom_point()
df %>%
pivot_longer(1:2, names_to = "var", values_to = "val") %>%
mutate(x = 1:n()) %>%
ggplot(aes(x = x, y = val, color = var)) +
geom_point()
set.seed(1)
df = tibble(
x = 1:4,
a = c(1,4,3,7),
b = a + rnorm(4)
)
df %>%
pivot_longer(-x, names_to = "var", values_to = "val") %>%
mutate(x = 1:n()) %>%
ggplot(aes(x = x, y = val, color = var)) +
geom_point()
df %>%
pivot_longer(-x, names_to = "var", values_to = "val") %>%
ggplot(aes(x = x, y = val, color = var)) +
geom_point()
?geom_ribbon
df %>%
pivot_longer(-x, names_to = "var", values_to = "val")
df %>%
pivot_longer(-x, names_to = "var", values_to = "val") %>%
ggplot(aes(x = x, y = val, color = var)) +
geom_point() +
geom_ribbon(ymin = min(val), ymax = max(val))
df %>%
pivot_longer(-x, names_to = "var", values_to = "val") %>%
ggplot(aes(x = x, y = val, color = var)) +
geom_point() +
geom_ribbon(aes(ymin = min(val), ymax = max(val)))
df %>%
pivot_longer(-x, names_to = "var", values_to = "val") %>%
ggplot(aes(x = x, y = val, color = var)) +
geom_point() +
geom_ribbon(aes(ymin = val, ymax = val))
df
df %>%
ggplot(aes(x = x)) +
geom_ribbon(aes(ymin = a, ymax = b))
df %>%
ggplot(aes(x = x)) +
geom_errorbar(aes(ymin = a, ymax = b))
df %>%
pivot_longer(-x, names_to = "var", values_to = "val")
df %>%
pivot_longer(-x, names_to = "var", values_to = "val") %>%
ggplot(aes(x = x, y = val)) +
geom_line()
df %>%
pivot_longer(-x, names_to = "var", values_to = "val") %>%
ggplot(aes(x = x, y = val, color = var)) +
geom_line()
df %>%
pivot_longer(-x, names_to = "var", values_to = "val") %>%
ggplot(aes(x = x, y = val, color = var)) +
geom_vline()
?kmeans
36170/1228
36170/1338
library(tidyverse)
install.packages("D:/gurobi950/win64/R/gurobi_9.5-0.zip", repos = NULL, type = "win.binary")
install.packages("slam")
library(gurobi)
library(gurobi)
model = list()
model$A = matrix(c(1,1,0,0,1,1), nrow = 2, byrow = TRUE)
model$obj = c(1,2,3)
model$modelsense = "max"
model$rhs = c(1,1)
model$sense = c("<=", "<=")
result = gurobi(model)
result$objval
?c_across
library(tidyverse)
?c_across
library(mlr3verse)
library(mlr3proba)
library(survival)
task = tsk("rats")
learner = lrn("surv.coxh")
learner = lrn("surv.coxph")
measure = msr("surv.hung_auc")
install.packages("survAUC")
measure = msr("surv.hung_auc")
pred = learner$train(task)$predict(task)
pred$score(measure)
measure = msr("surv.cindex")
pred$score(measure)
measure = msr("surv.hung_auc", times = 60)
pred$score(measure, task)
task$data()
pred$score(measure, task, row_ids = 1:270)
pred = learner$train(task, row_ids = 1:270)$predict(task, row_ids = 271:300)
pred$score(measure, task)
pred$score(measure, task, train_set = 1:270)
pred = learner$train(task)$predict(task)
pred$score(measure, task, train_set = 1:270)
?survAUC::AUC.hc()
learner = lrn("surv.coxph")
measure = msr("surv.hung_auc", times = 60)
pred = learner$train(task, row_ids = 1:270)$predict(task, row_ids = 271:300)
pred$score(measure, task, train_set = 1:270)
library(tidyverse)
?mean
df = tibble(
x = c(2,NA,5,7),
y = LETTERS[1:4],
z = c(5,6,NA,NA)
)
df
df %>%
mutate(across(where(is.numeric), ~ .x[is.na(.x)] = mean(.x, na.rm = TRUE)))
?replace_na
starwars %>%
mutate(across(where(is.numeric)), ~ replace_na(.x, mean(.x, na.rm = TRUE)))
starwars %>%
mutate(across(where(is.numeric), ~ replace_na(.x, mean(.x, na.rm = TRUE))))
library(tinytex)
pdflatex("mcmthesis.tex")
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex(mcmthesis-demo.tex)
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
library(timetk)
holidays <- tk_make_holiday_sequence(
start_date = "2013-01-01",
end_date   = "2013-12-31",
calendar   = "NYSE")
holidays
idx <- tk_make_weekday_sequence("2012",
remove_weekends = TRUE,
remove_holidays = TRUE, calendar = "NYSE")
idx
tk_get_timeseries_summary(idx)
idx <- tk_make_weekday_sequence("2012",
remove_weekends = TRUE,
remove_holidays = TRUE, calendar = "NYSE")
tk_get_timeseries_summary(idx)
tk_make_holiday_sequence("2012", calendar = "NYSE")
?tk_make_weekday_sequence
?slidify
FB <- FANG %>% filter(symbol == "FB")
library(tidyverse)
library(tidyquant)
FB <- FANG %>% filter(symbol == "FB")
mean_roll_5 <- slidify(mean, .period = 5, .align = "right")
FB %>%
mutate(rolling_mean_5 = mean_roll_5(adjusted))
as_mapper(~ .x ^ 2 + 1)
?roll_toslide
?roll_tos_lide
?roll_to_slide
?pslide
remove.packages("timetk")
install.packages("timetk")
install.packages("timetk")
idx <- tk_make_weekday_sequence("2012",
remove_weekends = TRUE,
remove_holidays = TRUE, calendar = "NYSE")
tk_get_timeseries_summary(idx)
library(timetk)
idx <- tk_make_weekday_sequence("2012",
remove_weekends = TRUE,
remove_holidays = TRUE, calendar = "NYSE")
tk_get_timeseries_summary(idx)
?tk_make_weekday_sequence
holidays <- tk_make_holiday_sequence(
start_date = "2016",
end_date   = "2017",
calendar   = "NYSE")
weekends <- tk_make_weekend_sequence(
start_date = "2016",
end_date   = "2017")
holidays
weekends
weekends <- tk_make_weekend_sequence(
start_date = "2016-01-01",
end_date   = "2017-12-31")
weekends
weekends <- tk_make_weekdays_sequence(
start_date = "2016-01-01",
end_date   = "2017-12-31")
weekends <- tk_make_weekday_sequence(
start_date = "2016-01-01",
end_date   = "2017-12-31")
weekends
library(tinytex)
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
library(lubridate)
begin = ymd_hm("2019-08-10 14:00")
end = ymd_hm("2020-03-05 18:15")
interval(begin, end)
begin %--% end
library(tinytex)
xelatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("MCM-ICM_Summary.tex")
pdflatex("MCM-ICM_Summary.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
library(tidyverse)
df = tribble(
~A, ~B
北京, 上海
df = tribble(
~A, ~B,
北京, 上海
南京, 西安
df = tribble(
~A, ~B,
北京, 上海,
南京, 西安,
上海, 南京,
合肥, 沈阳,
上海, 北京,
上海, 南京,
西安, 南京,
天津, 广州)
?tribble
df = tribble(
~A, ~B,
北京, 上海,
南京, 西安,
上海, 南京,
合肥, 沈阳,
上海, 北京,
上海, 南京,
西安, 南京,
天津, 广州)
df = tribble(
~A, ~B,
"北京", "上海",
"南京", "西安",
"上海", "南京",
"合肥", "沈阳",
"上海", "北京",
"上海", "南京",
"西安", "南京",
"天津", "广州")
df
?distinct
library(sets)
install.packages("sets")
library(sets)
df %>%
mutate(C = set(A, B))
df = tibble(x = c(1:3,3:1,4), y = c(2,4,4,2,1,2,1))
library(tidyverse)
df = tibble(x = c(1:3,3:1,4), y = c(2,4,4,2,1,2,1))
df
library(tidyverse)
df = tibble(x = c(1:3,3:1,4), y = c(2,4,4,2,1,2,1))
df
f = function(...) {
dummy = rep(0, 4)
dummy[c(...)] = 1
dummy
}
df = tibble(x = c(1:3,3:1,NA), y = c(2,4,4,2,1,2,1))
df
f = function(...) {
dummy = rep(NA, 4)
dummy[c(...)] = 1
dummy
}
df %>%
mutate(z = pmap(., f)) %>%
unnest_wider(z, names_sep = "")
f = function(...) {
v = c(...)
dummy = ifelse(any(is.na(v)), rep(NA, 4), rep(0,4))
dummy[v] = 1
dummy
}
df %>%
mutate(z = pmap(., f)) %>%
unnest_wider(z, names_sep = "")
df
f = function(...) {
v = c(...)
dummy = ifelse(any(is.na(v)), rep(NA,4), rep(0,4))
dummy[v] = 1
dummy
}
df %>%
mutate(z = pmap(., f)) %>%
unnest_wider(z, names_sep = "")
v = c(NA, 1)
any(is.na(v))
dummy = rep(NA, 4)
dummy[v]
dummy[!is.na(v)]
vv
v
dummy[v] = 1
dummy
v = c(2,4)
any(is.na(v))
dummy = rep(0,4)
dummy
dummy[v] = 1
dummy
df
f(1,2)
f(1,NA)
f(c(1,2))
df
v = c(2,4)
dummy = ifelse(any(is.na(v)), rep(NA,4), rep(0,4))
dummy
any(is.na(v))
rep(0,4)
rep(NA,4)
is.na(v)
v = c(2.4)
v = c(2,4)
dummy = ifelse(any(is.na(v)), rep(NA,4), rep(0,4))
any(is.na(v))
ifelse(any(is.na(v)), rep(NA,4), rep(0,4))
ifelse(any(is.na(v)), rep(NA,4), rep(0,4))
if(any(is.na(v)) rep(NA,4)
if(any(is.na(v))) rep(NA,4)
else rep(0,4)
if(any(is.na(v))) dummy = rep(NA,4)
else dummy = rep(0,4)
if(any(is.na(v))) {
dummy = rep(NA,4)
} else {
dummy = rep(0,4)
}
f = function(...) {
v = c(...)
if(any(is.na(v))) {
dummy = rep(NA,4)
} else {
dummy = rep(0,4)
}
dummy[v] = 1
dummy
}
f(2,4)
f(1,2)
f(1,NA)
f(NA,4)
f = function(...) {
v = c(...)
if(any(is.na(v))) {
dummy = rep(NA,4)
} else {
dummy = rep(0,4)
}
dummy[v] = 1
dummy
}
df %>%
mutate(z = pmap(., f)) %>%
unnest_wider(z, names_sep = "")
f = function(...) {
v = c(...)
dummy = ifelse(any(is.na(v)), rep(NA,4), rep(0,4))
dummy[v] = 1
dummy
}
df %>%
mutate(z = pmap(., f)) %>%
unnest_wider(z, names_sep = "")
f = function(...) {
v = c(...)
dummy = ifelse(all(!is.na(v)), rep(0,4), rep(NA,4))
dummy[v] = 1
dummy
}
df %>%
mutate(z = pmap(., f)) %>%
unnest_wider(z, names_sep = "")
v = c(2,4)
ifelse(all(!is.na(v)), rep(0,4), rep(NA,4))
rep(0,4)
3827.64 / 600
(3827.64 - 800) * 0.2 * 0.7
(3827.64 - 423.87) / 600
5103.51 * 0.8 * 0.2 * 0.7
(5103.51 - 571.59) / 800
12758.78 * 0.8 * 0.2 * 0.7
(12758.78 - 1428.98) / 2000
df = tibble(x = c(1:3,3:1,NA), y = c(2,4,NA,2,1,2,1))
df
f = function(...) {
v = c(...)
if(any(is.na(v))) {
dummy = rep(NA,4)
} else {
dummy = rep(0,4)
}
dummy[v] = 1
dummy
}
df %>%
mutate(z = pmap(., f)) %>%
unnest_wider(z, names_sep = "")
df = tibble(x = c(1:3,3:1,NA), y = c(2,4,NA,2,1,2,NA))
df
f = function(...) {
v = c(...)
if(any(is.na(v))) {
dummy = rep(NA,4)
} else {
dummy = rep(0,4)
}
dummy[v] = 1
dummy
}
df %>%
mutate(z = pmap(., f)) %>%
unnest_wider(z, names_sep = "")
df
df %>%
mutate(z = pmap(., f)) %>%
unnest_wider(z, names_sep = "")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
3827.63 / 600
5.67 / 6.38
80000 * 0.8887147
library(tinytex)
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
library(tinytex)
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex")
pdflatex("mcmthesis-demo.tex", bib_engine = "biber")
pdflatex("mcmthesis-demo.tex", bib_engine = "biber")
library(tinytex)
pdflatex("mcmthesis-demo.tex", bib_engine = "biber")
pdflatex("mcmthesis-demo.tex", bib_engine = "biber")
pdflatex("mcmthesis-demo.tex", bib_engine = "biber")
pdflatex("mcmthesis-demo.tex", bib_engine = "biber")
pdflatex("mcmthesis-demo.tex", bib_engine = "biber")
library(tinytex)
pdflatex("mcmthesis-demo.tex", bib_engine = "biber")