test_that("wave.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.modwt <- brick.wall(modwt(returns[,"DEM.USD"], wf, J), wf)
jpyusd.modwt <- brick.wall(modwt(returns[,"JPY.USD"], wf, J), wf)
rand.modwt <- brick.wall(modwt(rnorm(length(returns[,"DEM.USD"])), wf, J), wf)
##xx <- list(demusd.modwt.bw, jpyusd.modwt.bw)
xx <- list(demusd.modwt, jpyusd.modwt, rand.modwt)
names(xx) <- c("DEM.USD","JPY.USD","rand")
# ---------------------------
Lst <- wave.multiple.cross.correlation(xx, lag.max=lmax) #, ymaxr=NULL)
expect_true(is.list(Lst))
# ---------------------------
Lst <- wave.multiple.cross.regression(xx, lag.max=lmax) #, ymaxr=NULL)
expect_true(is.list(Lst))
# ---------------------------
Lst <- wave.multiple.cross.correlation(xx, lag.max=lmax, ymaxr=1)
expect_true(is.list(Lst))
# ---------------------------
Lst <- wave.multiple.cross.regression(xx, lag.max=lmax, ymaxr=1)
expect_true(is.list(Lst))
})
test_that("plot_WMCC and plot_WLMCR work with ymax=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.modwt <- brick.wall(modwt(returns[,"DEM.USD"], wf, J), wf)
jpyusd.modwt <- brick.wall(modwt(returns[,"JPY.USD"], wf, J), wf)
rand.modwt <- brick.wall(modwt(rnorm(length(returns[,"DEM.USD"])), wf, J), wf)
xx <- list(demusd.modwt, jpyusd.modwt, rand.modwt)
names(xx) <- c("DEM.USD","JPY.USD","rand")
Lst <- wave.multiple.cross.regression(xx, lag.max=lmax) #, ymaxr=1)
# ---------------------------
##Producing cross-correlation heat map
expect_null(
heatmap_wave.multiple.cross.correlation(Lst, lmax, ci=NULL) #, pdf.write=NULL)
)
expect_null(
heatmap_wave.multiple.cross.correlation(Lst, lmax, ci="center") #, pdf.write=NULL)
)
expect_null(
heatmap_wave.multiple.cross.correlation(Lst, lmax, ci="lower") #, pdf.write=NULL)
)
expect_null(
heatmap_wave.multiple.cross.correlation(Lst, lmax, ci="upper") #, pdf.write=NULL)
)
expect_error(
heatmap_wave.multiple.cross.correlation(Lst, lmax, ci="other") #, pdf.write=NULL)
)
# ---------------------------
##Producing cross-correlation plot
expect_null(
plot_wave.multiple.cross.correlation(Lst, lmax)
)
##Producing cross-regression plot
expect_null(
plot_wave.multiple.cross.regression(Lst, lmax, nsig=2)
)
##Producing cross-correlation plot
expect_error(
plot_wave.multiple.cross.correlation(Lst, lmax, xaxt="blah")
)
##Producing cross-regression plot
expect_error(
plot_wave.multiple.cross.regression(Lst, lmax, nsig=2, xaxt="blah")
)
# ---------------------------
})
test_that("plot_WMCC and plot_WLMCR work with ymax=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.modwt <- brick.wall(modwt(returns[,"DEM.USD"], wf, J), wf)
jpyusd.modwt <- brick.wall(modwt(returns[,"JPY.USD"], wf, J), wf)
rand.modwt <- brick.wall(modwt(rnorm(length(returns[,"DEM.USD"])), wf, J), wf)
xx <- list(demusd.modwt, jpyusd.modwt, rand.modwt)
names(xx) <- c("DEM.USD","JPY.USD","rand")
Lst <- wave.multiple.cross.regression(xx, lag.max=lmax, ymaxr=1)
# ---------------------------
##Producing cross-correlation heat map
expect_null(
heatmap_wave.multiple.cross.correlation(Lst, lmax, ci=NULL) #, pdf.write=NULL)
)
expect_null(
heatmap_wave.multiple.cross.correlation(Lst, lmax, ci="center") #, pdf.write=NULL)
)
expect_null(
heatmap_wave.multiple.cross.correlation(Lst, lmax, ci="lower") #, pdf.write=NULL)
)
expect_null(
heatmap_wave.multiple.cross.correlation(Lst, lmax, ci="upper") #, pdf.write=NULL)
)
expect_error(
heatmap_wave.multiple.cross.correlation(Lst, lmax, ci="other") #, pdf.write=NULL)
)
# ---------------------------
##Producing cross-correlation plot
expect_null(
plot_wave.multiple.cross.correlation(Lst, lmax)
)
##Producing cross-regression plot
expect_null(
plot_wave.multiple.cross.regression(Lst, lmax, nsig=2)
)
##Producing cross-correlation plot
expect_error(
plot_wave.multiple.cross.correlation(Lst, lmax, xaxt="blah")
)
##Producing cross-regression plot
expect_error(
plot_wave.multiple.cross.regression(Lst, lmax, nsig=2, xaxt="blah")
)
# ---------------------------
})
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