CRAN Package Check Results for Package portes

Last updated on 2022-05-18 07:49:05 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 5.0 10.09 111.24 121.33 ERROR
r-devel-linux-x86_64-debian-gcc 5.0 7.78 82.74 90.52 ERROR
r-devel-linux-x86_64-fedora-clang 5.0 142.53 ERROR
r-devel-linux-x86_64-fedora-gcc 5.0 80.90 ERROR
r-devel-windows-x86_64 5.0 21.00 150.00 171.00 OK
r-patched-linux-x86_64 5.0 10.67 104.34 115.01 ERROR
r-release-linux-x86_64 5.0 11.55 102.44 113.99 ERROR
r-release-macos-arm64 5.0 38.00 OK
r-release-macos-x86_64 5.0 75.00 OK
r-release-windows-x86_64 5.0 22.00 152.00 174.00 OK
r-oldrel-macos-arm64 5.0 47.00 OK
r-oldrel-macos-x86_64 5.0 70.00 OK
r-oldrel-windows-ix86+x86_64 5.0 24.00 133.00 157.00 OK

Check Details

Version: 5.0
Check: package dependencies
Result: NOTE
    Package suggested but not available for checking: 'FitAR'
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 5.0
Check: Rd cross-references
Result: NOTE
    Unknown package 'FitAR' in Rd xrefs
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 5.0
Check: examples
Result: ERROR
    Running examples in 'portes-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: BoxPierce
    > ### Title: The Univariate-Multivariate Box and Pierce Portmanteau Test
    > ### Aliases: BoxPierce
    > ### Keywords: Portmanteau Test
    >
    > ### ** Examples
    >
    > x <- rnorm(100)
    > BoxPierce(x) ## univariate test
     lags statistic df p-value
     5 3.365573 5 0.6438184
     10 5.656600 10 0.8432421
     15 6.411116 15 0.9719842
     20 10.784097 20 0.9516304
     25 14.805770 25 0.9458056
     30 18.070877 30 0.9573747
    > x <- cbind(rnorm(100),rnorm(100))
    > BoxPierce(x) ## multivariate test
     lags statistic df p-value
     5 21.57526 20 0.3639953
     10 46.56519 40 0.2203640
     15 68.17104 60 0.2192425
     20 80.06079 80 0.4770587
     25 93.89001 100 0.6531214
     30 109.78629 120 0.7374883
    > ##
    > ##
    > ## Annual flow of the river Nile at Aswan - 1871 to 1970
    > fit <- arima(Nile, c(1, 0, 1))
    > lags <- c(5, 10, 20)
    > ## Apply the univariate test statistic on the fitted model
    > BoxPierce(fit, lags) ## Correct (no need to specify order)
     lags statistic df p-value
     5 1.278883 3 0.7341534
     10 9.002228 8 0.3421081
     20 12.767895 18 0.8051730
    > BoxPierce(fit, lags, order = 2) ## Correct
     lags statistic df p-value
     5 1.278883 3 0.7341534
     10 9.002228 8 0.3421081
     20 12.767895 18 0.8051730
    > ## Apply the test statistic on the residuals and set order = 2
    > res <- resid(fit)
    > BoxPierce(res, lags) ## Wrong (order is needed!)
     lags statistic df p-value
     5 1.278883 5 0.9370895
     10 9.002228 10 0.5318922
     20 12.767895 20 0.8871190
    > BoxPierce(res, lags, order = 2) ## Correct
     lags statistic df p-value
     5 1.278883 3 0.7341534
     10 9.002228 8 0.3421081
     20 12.767895 18 0.8051730
    > ##
    > ##
    > ## Quarterly, west German investment, income, and consumption from 1960 Q1 to 1982 Q4
    > data(WestGerman)
    > DiffData <- matrix(numeric(3 * 91), ncol = 3)
    > for (i in 1:3)
    + DiffData[, i] <- diff(log(WestGerman[, i]), lag = 1)
    > fit <- ar.ols(DiffData, intercept = TRUE, order.max = 2)
    > lags <- c(5,10)
    > ## Apply the test statistic on the fitted model
    > BoxPierce(fit,lags) ## Correct (no need to specify order)
     lags statistic df p-value
     5 29.13889 27 0.3541968
     10 66.82771 72 0.6502032
    > ## Apply the test statistic on the residuals where order = 2
    > res <- ts((fit$resid)[-(1:2), ])
    > BoxPierce(res,lags) ## Wrong (order is needed!)
     lags statistic df p-value
     5 29.13889 45 0.9678196
     10 66.82771 90 0.9679689
    > BoxPierce(res,lags,order = 2) ## Correct
     lags statistic df p-value
     5 29.13889 27 0.3541968
     10 66.82771 72 0.6502032
    > ##
    > ##
    > ## Monthly log stock returns of Intel corporation data: Test for ARCH Effects
    > monthintel <- as.ts(monthintel)
    > BoxPierce(monthintel) ## Usual test
     lags statistic df p-value
     5 4.666889 5 0.45786938
     10 14.364748 10 0.15699489
     15 23.120348 15 0.08161787
     20 24.000123 20 0.24238680
     25 29.617977 25 0.23891229
     30 31.943703 30 0.37015020
    > BoxPierce(monthintel,squared.residuals=TRUE) ## Test for ARCH effects
     lags statistic df p-value
     5 40.78073 5 1.039009e-07
     10 49.57872 10 3.189915e-07
     15 81.90133 15 3.131517e-11
     20 86.50575 20 3.006796e-10
     25 87.54737 25 7.161478e-09
     30 88.55017 30 1.087505e-07
    > ##
    > ##
    > ## Test for seasonality
    > ## Accidental Deaths in the US 1973 - 1978
    > seasonal.arima <- arima(USAccDeaths, order = c(0,1,1), seasonal = list(order = c(0,1,1)))
    > BoxPierce(seasonal.arima, lags = 5, season = 12)
     lags statistic df p-value
     5 0.5845238 3 0.899966
    > ## Quarterly U.K. economic time series from 1957 Q3 to 1967 Q4
    > cd <- EconomicUK[,1]
    > cd.fit <- arima(cd,order=c(0,1,0),seasonal=list(order=c(0,1,1),period=4))
    > BoxPierce(cd.fit, lags = c(5,10), season = 4)
     lags statistic df p-value
     5 1.307341 4 0.8601288
     10 1.918594 9 0.9926904
    > ##
    > ##
    > #### Write a function to fit a model: Apply portmanteau test on fitted obj with class "list"
    > ## Example 1
    > require("FitAR")
    Loading required package: FitAR
    Warning in library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, :
     there is no package called 'FitAR'
    > FitModel <- function(data){
    + fit <- FitAR(z=data,p=2)
    + p <- length(fit$phiHat)
    + order <- p
    + res <- fit$res
    + list(res=res,order=order)
    + }
    > Fit <- FitModel(Nile)
    Error in FitAR(z = data, p = 2) : could not find function "FitAR"
    Calls: FitModel
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 5.0
Check: Rd cross-references
Result: NOTE
    Undeclared package ‘TSA’ in Rd xrefs
    Unknown package ‘FitAR’ in Rd xrefs
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 5.0
Check: examples
Result: ERROR
    Running examples in ‘portes-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: BoxPierce
    > ### Title: The Univariate-Multivariate Box and Pierce Portmanteau Test
    > ### Aliases: BoxPierce
    > ### Keywords: Portmanteau Test
    >
    > ### ** Examples
    >
    > x <- rnorm(100)
    > BoxPierce(x) ## univariate test
     lags statistic df p-value
     5 3.365573 5 0.6438184
     10 5.656600 10 0.8432421
     15 6.411116 15 0.9719842
     20 10.784097 20 0.9516304
     25 14.805770 25 0.9458056
     30 18.070877 30 0.9573747
    > x <- cbind(rnorm(100),rnorm(100))
    > BoxPierce(x) ## multivariate test
     lags statistic df p-value
     5 21.57526 20 0.3639953
     10 46.56519 40 0.2203640
     15 68.17104 60 0.2192425
     20 80.06079 80 0.4770587
     25 93.89001 100 0.6531214
     30 109.78629 120 0.7374883
    > ##
    > ##
    > ## Annual flow of the river Nile at Aswan - 1871 to 1970
    > fit <- arima(Nile, c(1, 0, 1))
    > lags <- c(5, 10, 20)
    > ## Apply the univariate test statistic on the fitted model
    > BoxPierce(fit, lags) ## Correct (no need to specify order)
     lags statistic df p-value
     5 1.278883 3 0.7341534
     10 9.002228 8 0.3421081
     20 12.767895 18 0.8051730
    > BoxPierce(fit, lags, order = 2) ## Correct
     lags statistic df p-value
     5 1.278883 3 0.7341534
     10 9.002228 8 0.3421081
     20 12.767895 18 0.8051730
    > ## Apply the test statistic on the residuals and set order = 2
    > res <- resid(fit)
    > BoxPierce(res, lags) ## Wrong (order is needed!)
     lags statistic df p-value
     5 1.278883 5 0.9370895
     10 9.002228 10 0.5318922
     20 12.767895 20 0.8871190
    > BoxPierce(res, lags, order = 2) ## Correct
     lags statistic df p-value
     5 1.278883 3 0.7341534
     10 9.002228 8 0.3421081
     20 12.767895 18 0.8051730
    > ##
    > ##
    > ## Quarterly, west German investment, income, and consumption from 1960 Q1 to 1982 Q4
    > data(WestGerman)
    > DiffData <- matrix(numeric(3 * 91), ncol = 3)
    > for (i in 1:3)
    + DiffData[, i] <- diff(log(WestGerman[, i]), lag = 1)
    > fit <- ar.ols(DiffData, intercept = TRUE, order.max = 2)
    > lags <- c(5,10)
    > ## Apply the test statistic on the fitted model
    > BoxPierce(fit,lags) ## Correct (no need to specify order)
     lags statistic df p-value
     5 29.13889 27 0.3541968
     10 66.82771 72 0.6502032
    > ## Apply the test statistic on the residuals where order = 2
    > res <- ts((fit$resid)[-(1:2), ])
    > BoxPierce(res,lags) ## Wrong (order is needed!)
     lags statistic df p-value
     5 29.13889 45 0.9678196
     10 66.82771 90 0.9679689
    > BoxPierce(res,lags,order = 2) ## Correct
     lags statistic df p-value
     5 29.13889 27 0.3541968
     10 66.82771 72 0.6502032
    > ##
    > ##
    > ## Monthly log stock returns of Intel corporation data: Test for ARCH Effects
    > monthintel <- as.ts(monthintel)
    > BoxPierce(monthintel) ## Usual test
     lags statistic df p-value
     5 4.666889 5 0.45786938
     10 14.364748 10 0.15699489
     15 23.120348 15 0.08161787
     20 24.000123 20 0.24238680
     25 29.617977 25 0.23891229
     30 31.943703 30 0.37015020
    > BoxPierce(monthintel,squared.residuals=TRUE) ## Test for ARCH effects
     lags statistic df p-value
     5 40.78073 5 1.039009e-07
     10 49.57872 10 3.189915e-07
     15 81.90133 15 3.131517e-11
     20 86.50575 20 3.006796e-10
     25 87.54737 25 7.161478e-09
     30 88.55017 30 1.087505e-07
    > ##
    > ##
    > ## Test for seasonality
    > ## Accidental Deaths in the US 1973 - 1978
    > seasonal.arima <- arima(USAccDeaths, order = c(0,1,1), seasonal = list(order = c(0,1,1)))
    > BoxPierce(seasonal.arima, lags = 5, season = 12)
     lags statistic df p-value
     5 0.5845238 3 0.899966
    > ## Quarterly U.K. economic time series from 1957 Q3 to 1967 Q4
    > cd <- EconomicUK[,1]
    > cd.fit <- arima(cd,order=c(0,1,0),seasonal=list(order=c(0,1,1),period=4))
    > BoxPierce(cd.fit, lags = c(5,10), season = 4)
     lags statistic df p-value
     5 1.307341 4 0.8601288
     10 1.918594 9 0.9926904
    > ##
    > ##
    > #### Write a function to fit a model: Apply portmanteau test on fitted obj with class "list"
    > ## Example 1
    > require("FitAR")
    Loading required package: FitAR
    Warning in library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, :
     there is no package called ‘FitAR’
    > FitModel <- function(data){
    + fit <- FitAR(z=data,p=2)
    + p <- length(fit$phiHat)
    + order <- p
    + res <- fit$res
    + list(res=res,order=order)
    + }
    > Fit <- FitModel(Nile)
    Error in FitAR(z = data, p = 2) : could not find function "FitAR"
    Calls: FitModel
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc