Nothing
test_that("local.multiple.cross.* works", {
data(exchange)
returns <- diff(log(exchange))
returns <- ts(returns, start=1970, freq=12)
N <- dim(returns)[1]
# wf <- "d4"
M <- 10
window <- "gauss"
# J <- trunc(log2(N))-3
lmax <- 1
set.seed(140859)
demusd <- returns[,"DEM.USD"]
jpyusd <- returns[,"JPY.USD"]
rand <- rnorm(length(returns[,"DEM.USD"]))
##xx <- list(demusd, jpyusd)
xx <- data.frame(demusd, jpyusd, rand)
names(xx) <- c("DEM.USD","JPY.USD","rand")
# ---------------------------
Lst <- local.multiple.cross.correlation(xx, M, window=window, lag.max=lmax) #, ymaxr=NULL)
expect_true(is.list(Lst))
# ---------------------------
Lst <- local.multiple.cross.regression(xx, M, window=window, lag.max=lmax) #, ymaxr=NULL)
expect_true(is.list(Lst))
# ---------------------------
Lst <- local.multiple.cross.correlation(xx, M, window=window, lag.max=lmax, ymaxr=1)
expect_true(is.list(Lst))
# ---------------------------
Lst <- local.multiple.cross.regression(xx, M, window=window, lag.max=lmax, ymaxr=1)
expect_true(is.list(Lst))
})
test_that("plot_LMCC and plot_LMCR work with ymaxr=NULL", {
data(exchange)
returns <- diff(log(exchange))
returns <- ts(returns, start=1970, freq=12)
N <- dim(returns)[1]
# wf <- "d4"
M <- 10
window <- "gauss"
# J <- trunc(log2(N))-3
lmax <- 1
set.seed(140859)
demusd <- returns[,"DEM.USD"]
jpyusd <- returns[,"JPY.USD"]
rand <- rnorm(length(returns[,"DEM.USD"]))
##xx <- list(demusd, jpyusd)
xx <- data.frame(demusd, jpyusd, rand)
names(xx) <- c("DEM.USD","JPY.USD","rand")
# Note: WLMCR may take more than 10 seconds of CPU time on some systems
Lst <- local.multiple.cross.regression(xx, M, window=window, lag.max=lmax) #, ymaxr=1)
# ---------------------------
#xaxt NULL
##Producing cross-correlation plot
expect_null(
plot_local.multiple.cross.correlation(Lst, lmax) #, xaxt="s")
)
##Producing cross-regression plot
expect_null(
plot_local.multiple.cross.regression(Lst, lmax, nsig=2) #, xaxt="s")
)
# ---------------------------
#xaxt ="s"
##Producing cross-correlation plot
expect_null(
plot_local.multiple.cross.correlation(Lst, lmax, xaxt="s")
)
##Producing cross-regression plot
expect_null(
plot_local.multiple.cross.regression(Lst, lmax, nsig=2, xaxt="s")
)
# ---------------------------
#xaxt a list(at=,label=)
xaxt <- list(at=seq(1,5),label=paste0(seq(1,5)))
##Producing cross-correlation plot
expect_null(
plot_local.multiple.cross.correlation(Lst, lmax, xaxt=xaxt)
)
##Producing cross-regression plot
expect_null(
plot_local.multiple.cross.regression(Lst, lmax, nsig=2, xaxt=xaxt)
)
# ---------------------------
#xaxt a list anything else
xaxt <- list(at=seq(1,5),label=paste0(seq(1,5)))
##Producing cross-correlation plot
expect_error(
plot_local.multiple.cross.correlation(Lst, lmax, xaxt="blah")
)
##Producing cross-regression plot
expect_error(
plot_local.multiple.cross.regression(Lst, lmax, nsig=2, xaxt="blah")
)
})
test_that("plot_LMCC and plot_LMCR work with ymaxr=1", {
data(exchange)
returns <- diff(log(exchange))
returns <- ts(returns, start=1970, freq=12)
N <- dim(returns)[1]
# wf <- "d4"
M <- 10
window <- "gauss"
# J <- 1 #trunc(log2(N))-3
lmax <- 1
set.seed(140859)
demusd <- returns[,"DEM.USD"]
jpyusd <- returns[,"JPY.USD"]
rand <- rnorm(length(returns[,"DEM.USD"]))
##xx <- list(demusd, jpyusd)
xx <- data.frame(demusd, jpyusd, rand)
names(xx) <- c("DEM.USD","JPY.USD","rand")
# Note: WLMCR may take more than 10 seconds of CPU time on some systems
Lst <- local.multiple.cross.regression(xx, M, window=window, lag.max=lmax, ymaxr=1)
# ---------------------------
#xaxt NULL
##Producing cross-correlation plot
expect_null(
plot_local.multiple.cross.correlation(Lst, lmax) #, xaxt="s")
)
##Producing cross-regression plot
expect_null(
plot_local.multiple.cross.regression(Lst, lmax, nsig=2) #, xaxt="s")
)
# ---------------------------
#xaxt ="s"
##Producing cross-correlation plot
expect_null(
plot_local.multiple.cross.correlation(Lst, lmax, xaxt="s")
)
##Producing cross-regression plot
expect_null(
plot_local.multiple.cross.regression(Lst, lmax, nsig=2, xaxt="s")
)
# ---------------------------
#xaxt a list(at=,label=)
xaxt <- list(at=seq(1,5),label=paste0(seq(1,5)))
##Producing cross-correlation plot
expect_null(
plot_local.multiple.cross.correlation(Lst, lmax, xaxt=xaxt)
)
##Producing cross-regression plot
expect_null(
plot_local.multiple.cross.regression(Lst, lmax, nsig=2, xaxt=xaxt)
)
# ---------------------------
#xaxt a list anything else
xaxt <- list(at=seq(1,5),label=paste0(seq(1,5)))
##Producing cross-correlation plot
expect_error(
plot_local.multiple.cross.correlation(Lst, lmax, xaxt="blah")
)
##Producing cross-regression plot
expect_error(
plot_local.multiple.cross.regression(Lst, lmax, nsig=2, xaxt="blah")
)
})
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