df <- tibble::tibble(
f = c("rbinom", "rpois", "rnorm"),
params = list(
list(list(n = 5,size=2,prob=0.5), list(n = 10,size=5,prob=0.5)),
list(n = 5, lambda = 10),
list(n = 10, mean = -3, sd = 10)
)
)
df
invoke_map(df$f, df$params)
The above is my working example. What i want is to pass multiple arguments only to rbinom function. but this throws an error.. any help would be much appreciated
I think the problem is in your df shape.
This works:
library(tidyverse)
df <- tibble::tibble(
f = c("rbinom","rbinom", "rpois", "rnorm"),
params = list(
list(n = 5,size=2,prob=0.5),
list(n = 10,size=5,prob=0.5),
list(n = 5, lambda = 10),
list(n = 10, mean = -3, sd = 10)
)
)
df
invoke_map(df$f, df$params)Thanks a lot. I had thought this way. but wanted to minimise typing..
one more thing, can we get the names also for each? i mean the distribution names also in the ouput?
invoke_map(df$f, df$params) %>% set_names(df$f)Thats wonderfull... but on similar lines this doesn't work
<!-- language-all: lang-r -->
packages<-c("tidyverse","ARDL","stargazer","data.table","readxl","dint","fable","zoo",
"tseries","urca")
sapply(packages,library,character.only=T)
#> To cite ARDL in publications use:
#>
#> Kleanthis Natsiopoulos and Nickolaos Tzeremes (2020). ARDL: ARDL, ECM and Bounds-Test for Cointegration. R package version 0.1.0. University of Thessaly, Department of Economics. https://github.com/Natsiopoulos/ARDL.
#>
#> Please cite as:
#> Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.
#> R package version 5.2.2. https://CRAN.R-project.org/package=stargazer
#>
#> Attaching package: 'data.table'
#> The following objects are masked from 'package:dplyr':
#>
#> between, first, last
#> The following object is masked from 'package:purrr':
#>
#> transpose
#> Loading required package: fabletools
#>
#> Attaching package: 'zoo'
#> The following objects are masked from 'package:base':
#>
#> as.Date, as.Date.numeric
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
#> $tidyverse
#> [1] "forcats" "stringr" "dplyr" "purrr" "readr" "tidyr"
#> [7] "tibble" "ggplot2" "tidyverse" "stats" "graphics" "grDevices"
#> [13] "utils" "datasets" "methods" "base"
#>
#> $ARDL
#> [1] "ARDL" "forcats" "stringr" "dplyr" "purrr" "readr"
#> [7] "tidyr" "tibble" "ggplot2" "tidyverse" "stats" "graphics"
#> [13] "grDevices" "utils" "datasets" "methods" "base"
#>
#> $stargazer
#> [1] "stargazer" "ARDL" "forcats" "stringr" "dplyr" "purrr"
#> [7] "readr" "tidyr" "tibble" "ggplot2" "tidyverse" "stats"
#> [13] "graphics" "grDevices" "utils" "datasets" "methods" "base"
#>
#> $data.table
#> [1] "data.table" "stargazer" "ARDL" "forcats" "stringr"
#> [6] "dplyr" "purrr" "readr" "tidyr" "tibble"
#> [11] "ggplot2" "tidyverse" "stats" "graphics" "grDevices"
#> [16] "utils" "datasets" "methods" "base"
#>
#> $readxl
#> [1] "readxl" "data.table" "stargazer" "ARDL" "forcats"
#> [6] "stringr" "dplyr" "purrr" "readr" "tidyr"
#> [11] "tibble" "ggplot2" "tidyverse" "stats" "graphics"
#> [16] "grDevices" "utils" "datasets" "methods" "base"
#>
#> $dint
#> [1] "dint" "readxl" "data.table" "stargazer" "ARDL"
#> [6] "forcats" "stringr" "dplyr" "purrr" "readr"
#> [11] "tidyr" "tibble" "ggplot2" "tidyverse" "stats"
#> [16] "graphics" "grDevices" "utils" "datasets" "methods"
#> [21] "base"
#>
#> $fable
#> [1] "fable" "fabletools" "dint" "readxl" "data.table"
#> [6] "stargazer" "ARDL" "forcats" "stringr" "dplyr"
#> [11] "purrr" "readr" "tidyr" "tibble" "ggplot2"
#> [16] "tidyverse" "stats" "graphics" "grDevices" "utils"
#> [21] "datasets" "methods" "base"
#>
#> $zoo
#> [1] "zoo" "fable" "fabletools" "dint" "readxl"
#> [6] "data.table" "stargazer" "ARDL" "forcats" "stringr"
#> [11] "dplyr" "purrr" "readr" "tidyr" "tibble"
#> [16] "ggplot2" "tidyverse" "stats" "graphics" "grDevices"
#> [21] "utils" "datasets" "methods" "base"
#>
#> $tseries
#> [1] "tseries" "zoo" "fable" "fabletools" "dint"
#> [6] "readxl" "data.table" "stargazer" "ARDL" "forcats"
#> [11] "stringr" "dplyr" "purrr" "readr" "tidyr"
#> [16] "tibble" "ggplot2" "tidyverse" "stats" "graphics"
#> [21] "grDevices" "utils" "datasets" "methods" "base"
#>
#> $urca
#> [1] "urca" "tseries" "zoo" "fable" "fabletools"
#> [6] "dint" "readxl" "data.table" "stargazer" "ARDL"
#> [11] "forcats" "stringr" "dplyr" "purrr" "readr"
#> [16] "tidyr" "tibble" "ggplot2" "tidyverse" "stats"
#> [21] "graphics" "grDevices" "utils" "datasets" "methods"
#> [26] "base"
data.table::data.table(
diff_ln_CONS = c(0.00237844629410211,
0.00502011796238699,0.00521423828112666,0.00396556205407395,
-0.000355909666671872,0.00729047396775528),
diff_ln_INC = c(0.00498960353265465,
0.00683295933524053,0.00264198002337168,0.00513780756387416,
0.0034247231416793,0.000307124646656609),
diff_ln_INV = c(-0.00107337503873972,
0.00633568939107332,0.00708907876911269,0.0177891127645107,
-0.00817818531435588,0.00459563441501265)
)
#> diff_ln_CONS diff_ln_INC diff_ln_INV
#> 1: 0.0023784463 0.0049896035 -0.001073375
#> 2: 0.0050201180 0.0068329593 0.006335689
#> 3: 0.0052142383 0.0026419800 0.007089079
#> 4: 0.0039655621 0.0051378076 0.017789113
#> 5: -0.0003559097 0.0034247231 -0.008178185
#> 6: 0.0072904740 0.0003071246 0.004595634
#Unit root tests
work_table<-tibble(
test=c("ur.df","ur.ers"),
parms=list(
list(x=data_diff,type="none",selectlags="AIC"),
list(x=data_diff,type="DF-GLS",model="constant")
)
)
#> Error in eval_tidy(xs[[j]], mask): object 'data_diff' not found
invoke_map(work_table$test,work_table$parms)
#> Error in as_invoke_function(.f): object 'work_table' not found
<sup>Created on 2020-08-14 by the [reprex package](https://reprex.tidyverse.org) (v0.3.0)</sup>
did you mean to assign the data.table::data.table( above to the name data_diff ?
No. data_diff is the dataframe upon which I want to conduct those tests on.. and I want the results of those tests for all the variables in a tibble format
you posted an error that clearly shows data_diff does not exist in your environment (or did not at the time that you had run your code). You should review that.
packages<-c("tidyverse","ARDL","stargazer","data.table","readxl","dint","fable","zoo",
"tseries","urca")
sapply(packages,library,character.only=T)
#> To cite ARDL in publications use:
#>
#> Kleanthis Natsiopoulos and Nickolaos Tzeremes (2020). ARDL: ARDL, ECM and Bounds-Test for Cointegration. R package version 0.1.0. University of Thessaly, Department of Economics. https://github.com/Natsiopoulos/ARDL.
#>
#> Please cite as:
#> Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.
#> R package version 5.2.2. https://CRAN.R-project.org/package=stargazer
#>
#> Attaching package: 'data.table'
#> The following objects are masked from 'package:dplyr':
#>
#> between, first, last
#> The following object is masked from 'package:purrr':
#>
#> transpose
#> Loading required package: fabletools
#>
#> Attaching package: 'zoo'
#> The following objects are masked from 'package:base':
#>
#> as.Date, as.Date.numeric
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
#> $tidyverse
#> [1] "forcats" "stringr" "dplyr" "purrr" "readr" "tidyr"
#> [7] "tibble" "ggplot2" "tidyverse" "stats" "graphics" "grDevices"
#> [13] "utils" "datasets" "methods" "base"
#>
#> $ARDL
#> [1] "ARDL" "forcats" "stringr" "dplyr" "purrr" "readr"
#> [7] "tidyr" "tibble" "ggplot2" "tidyverse" "stats" "graphics"
#> [13] "grDevices" "utils" "datasets" "methods" "base"
#>
#> $stargazer
#> [1] "stargazer" "ARDL" "forcats" "stringr" "dplyr" "purrr"
#> [7] "readr" "tidyr" "tibble" "ggplot2" "tidyverse" "stats"
#> [13] "graphics" "grDevices" "utils" "datasets" "methods" "base"
#>
#> $data.table
#> [1] "data.table" "stargazer" "ARDL" "forcats" "stringr"
#> [6] "dplyr" "purrr" "readr" "tidyr" "tibble"
#> [11] "ggplot2" "tidyverse" "stats" "graphics" "grDevices"
#> [16] "utils" "datasets" "methods" "base"
#>
#> $readxl
#> [1] "readxl" "data.table" "stargazer" "ARDL" "forcats"
#> [6] "stringr" "dplyr" "purrr" "readr" "tidyr"
#> [11] "tibble" "ggplot2" "tidyverse" "stats" "graphics"
#> [16] "grDevices" "utils" "datasets" "methods" "base"
#>
#> $dint
#> [1] "dint" "readxl" "data.table" "stargazer" "ARDL"
#> [6] "forcats" "stringr" "dplyr" "purrr" "readr"
#> [11] "tidyr" "tibble" "ggplot2" "tidyverse" "stats"
#> [16] "graphics" "grDevices" "utils" "datasets" "methods"
#> [21] "base"
#>
#> $fable
#> [1] "fable" "fabletools" "dint" "readxl" "data.table"
#> [6] "stargazer" "ARDL" "forcats" "stringr" "dplyr"
#> [11] "purrr" "readr" "tidyr" "tibble" "ggplot2"
#> [16] "tidyverse" "stats" "graphics" "grDevices" "utils"
#> [21] "datasets" "methods" "base"
#>
#> $zoo
#> [1] "zoo" "fable" "fabletools" "dint" "readxl"
#> [6] "data.table" "stargazer" "ARDL" "forcats" "stringr"
#> [11] "dplyr" "purrr" "readr" "tidyr" "tibble"
#> [16] "ggplot2" "tidyverse" "stats" "graphics" "grDevices"
#> [21] "utils" "datasets" "methods" "base"
#>
#> $tseries
#> [1] "tseries" "zoo" "fable" "fabletools" "dint"
#> [6] "readxl" "data.table" "stargazer" "ARDL" "forcats"
#> [11] "stringr" "dplyr" "purrr" "readr" "tidyr"
#> [16] "tibble" "ggplot2" "tidyverse" "stats" "graphics"
#> [21] "grDevices" "utils" "datasets" "methods" "base"
#>
#> $urca
#> [1] "urca" "tseries" "zoo" "fable" "fabletools"
#> [6] "dint" "readxl" "data.table" "stargazer" "ARDL"
#> [11] "forcats" "stringr" "dplyr" "purrr" "readr"
#> [16] "tidyr" "tibble" "ggplot2" "tidyverse" "stats"
#> [21] "graphics" "grDevices" "utils" "datasets" "methods"
#> [26] "base"
data_diff<-tibble::tribble(
~diff_ln_CONS..diff_ln_INC..diff_ln_INV,
"1: 0.0023784463 0.0049896035 -0.001073375",
"2: 0.0050201180 0.0068329593 0.006335689",
"3: 0.0052142383 0.0026419800 0.007089079",
"4: 0.0039655621 0.0051378076 0.017789113",
"5: -0.0003559097 0.0034247231 -0.008178185",
"6: 0.0072904740 0.0003071246 0.004595634"
)
work_table<-tibble(
test=c("ur.df","ur.ers"),
parms=list(
list(x=data_diff,type="none",selectlags="AIC"),
list(x=data_diff,type="DF-GLS",model="constant")
)
)
invoke_map(work_table$test,work_table$parms)
#> Error in ur.df(x = structure(list(diff_ln_CONS..diff_ln_INC..diff_ln_INV = c("1: 0.0023784463 0.0049896035 -0.001073375", : unused argument (x = list(c("1: 0.0023784463 0.0049896035 -0.001073375", "2: 0.0050201180 0.0068329593 0.006335689", "3: 0.0052142383 0.0026419800 0.007089079", "4: 0.0039655621 0.0051378076 0.017789113", "5: -0.0003559097 0.0034247231 -0.008178185", "6: 0.0072904740 0.0003071246 0.004595634")))
Created on 2020-08-16 by the reprex package (v0.3.0)
I am sorry.. didnt quite notice it
I found there was a challenge in that the two ur functions take different required params, i.e. selectlags and model, so I found it convenient to make function wrappers to swallow dummy unused values for each alternate
packages<-c("tidyverse","urca")
sapply(packages,library,character.only=T)
data_diff<-tibble::tribble(
~diff_ln_CONS,~diff_ln_INC,~diff_ln_INV,
0.0023784463, 0.0049896035,-0.001073375 ,
0.0050201180, 0.0068329593, 0.006335689 ,
0.0052142383, 0.0026419800, 0.007089079 ,
0.0039655621, 0.0051378076, 0.017789113 ,
-0.0003559097, 0.0034247231,-0.008178185 ,
0.0072904740, 0.0003071246, 0.004595634
)
ur.dfx <-function(y,type,selectlags,model){
ur.df(y,type,selectlags,lags=1)
}
ur.ersx <-function(y,type,selectlags,model){
ur.ers(y,type,model,lag.max = 1)
}
(y <- map(data_diff,~enframe(.,name=NULL)))
(work_table0<-expand_grid(tibble(test=c("ur.dfx","ur.ersx"),
type = c("none","DF-GLS"),
selectlags = "AIC",
model="constant"),y))
(work_table <- mutate(rowwise(work_table0),
parms = list(list("type"=type,"selectlags"=selectlags,
"model"=model,
"y"=pull(y,value)))) %>% select(test,parms))
(map_results <- invoke_map(work_table$test,work_table$parms))Thats a nice solution.. however, we are not able to recognise which variable the test is for. I would have loved to have it printed too. i did something like this
packages<-c("tidyverse","urca","rlist")
sapply(packages,library,character.only=T)
#> $tidyverse
#> [1] "forcats" "stringr" "dplyr" "purrr" "readr" "tidyr"
#> [7] "tibble" "ggplot2" "tidyverse" "stats" "graphics" "grDevices"
#> [13] "utils" "datasets" "methods" "base"
#>
#> $urca
#> [1] "urca" "forcats" "stringr" "dplyr" "purrr" "readr"
#> [7] "tidyr" "tibble" "ggplot2" "tidyverse" "stats" "graphics"
#> [13] "grDevices" "utils" "datasets" "methods" "base"
#>
#> $rlist
#> [1] "rlist" "urca" "forcats" "stringr" "dplyr" "purrr"
#> [7] "readr" "tidyr" "tibble" "ggplot2" "tidyverse" "stats"
#> [13] "graphics" "grDevices" "utils" "datasets" "methods" "base"
data_diff<-tibble::tribble(
~diff_ln_CONS,~diff_ln_INC,~diff_ln_INV,
0.0023784463, 0.0049896035,-0.001073375 ,
0.0050201180, 0.0068329593, 0.006335689 ,
0.0052142383, 0.0026419800, 0.007089079 ,
0.0039655621, 0.0051378076, 0.017789113 ,
-0.0003559097, 0.0034247231,-0.008178185 ,
0.0072904740, 0.0003071246, 0.004595634
)
MY_LIST=apply(data[,5:7],2,function(x){
return(
list(
ur.df(x, type = "drift",selectlags = c("BIC")),
ur.df(x, type = "trend",selectlags = c("BIC")),
ur.df(x, type = "none",selectlags = c("BIC")),
summary(ur.pp(x,type = "Z-tau",model = "constant")),
summary(ur.pp(x,type = "Z-tau",model = "trend"))
)
)
})
#> Error in data[, 5:7]: object of type 'closure' is not subsettable
rand<-unlist(MY_LIST)
#> Error in unlist(MY_LIST): object 'MY_LIST' not found
nb<-rand %>% map_df(.,~data.table("Test Statistic"=round(.x@teststat,3),model=.x@model,
test=.x@test.name),.id="Variable")
#> Error in eval(lhs, parent, parent): object 'rand' not found
nb_crit<-rand %>% map_df(.,~data.table(crit_val=.x@cval,
model=.x@model,
test=.x@test.name),.id="Variable")
#> Error in eval(lhs, parent, parent): object 'rand' not found
Created on 2020-08-16 by the reprex package (v0.3.0)
the nb and nb_crit are the results i want. I coud'nt make it more appealing though. The issue is in nb_crit, it is not known for which statistic is the critical value. I
Thanks and regards
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