фильтрация списков по заданным c элементам списка

Question

У меня есть список, который содержит что-то вроде следующего:

$AKAM

    Augmented Dickey-Fuller Test

data:  Cl(.)
Dickey-Fuller = -3.6785, Lag order = 3, p-value = 0.03802
alternative hypothesis: stationary


$ALXN

    Augmented Dickey-Fuller Test

data:  Cl(.)
Dickey-Fuller = -2.9311, Lag order = 3, p-value = 0.2052
alternative hypothesis: stationary

Я хочу фильтровать на основе p-value. Я могу получить доступ к p-value используя: d$AKAM$p.value. Я хотел бы отфильтровать списки на основе критериев, что значение р <0,05. </p>

Данные:

d <- list(ABMD = structure(list(statistic = c(`Dickey-Fuller` = -2.88823930907752), 
    parameter = c(`Lag order` = 3), alternative = "stationary", 
    p.value = 0.222153876057991, method = "Augmented Dickey-Fuller Test", 
    data.name = "Cl(.)"), class = "htest"), ATVI = structure(list(
    statistic = c(`Dickey-Fuller` = -2.86560166108736), parameter = c(`Lag order` = 3), 
    alternative = "stationary", p.value = 0.231115731952747, 
    method = "Augmented Dickey-Fuller Test", data.name = "Cl(.)"), class = "htest"), 
    ADBE = structure(list(statistic = c(`Dickey-Fuller` = -2.91292875187715), 
        parameter = c(`Lag order` = 3), alternative = "stationary", 
        p.value = 0.212379749850693, method = "Augmented Dickey-Fuller Test", 
        data.name = "Cl(.)"), class = "htest"), AMD = structure(list(
        statistic = c(`Dickey-Fuller` = -3.46654255102478), parameter = c(`Lag order` = 3), 
        alternative = "stationary", p.value = 0.0592779965240372, 
        method = "Augmented Dickey-Fuller Test", data.name = "Cl(.)"), class = "htest"), 
    AKAM = structure(list(statistic = c(`Dickey-Fuller` = -3.67846516682619), 
        parameter = c(`Lag order` = 3), alternative = "stationary", 
        p.value = 0.0380202892654308, method = "Augmented Dickey-Fuller Test", 
        data.name = "Cl(.)"), class = "htest"), ALXN = structure(list(
        statistic = c(`Dickey-Fuller` = -2.93110833009175), parameter = c(`Lag order` = 3), 
        alternative = "stationary", p.value = 0.205182767184581, 
        method = "Augmented Dickey-Fuller Test", data.name = "Cl(.)"), class = "htest"))

Answer 1

Мы можем использовать Filter с base R

Filter(function(x) x$p.value < 0.05, d)
#$AKAM

#   Augmented Dickey-Fuller Test

#data:  Cl(.)
#Dickey-Fuller = -3.6785, Lag order = 3, p-value = 0.03802
#alternative hypothesis: stationary

---

Или с keep с purrr

library(purrr)
keep(d, ~ .x$p.value < 0.05)

Answer 2

sapply(d, function(x) x$p.value < 0.05)
#  ABMD  ATVI  ADBE   AMD  AKAM  ALXN 
# FALSE FALSE FALSE FALSE  TRUE FALSE 

Фильтр данных из списка

d[sapply(d, function(x) x$p.value < 0.05)]
# $AKAM
# 
# Augmented Dickey-Fuller Test
# 
# data:  Cl(.)
# Dickey-Fuller = -3.6785, Lag order = 3, p-value = 0.03802
# alternative hypothesis: stationary

Answer 3

Один вариант, включающий purrr, может быть:

discard(d, ~ .x$p.value > 0.05)

$AKAM

    Augmented Dickey-Fuller Test

data:  Cl(.)
Dickey-Fuller = -3.6785, Lag order = 3, p-value = 0.03802
alternative hypothesis: stationary