Description Usage Arguments Details Value Author(s) References See Also Examples
Test for a linear trend in variances.
1 2 3 4 5 6 7 8 9 10 11 12 | ltrend.test(
y,
group,
score = NULL,
location = c("median", "mean", "trim.mean"),
tail = c("right", "left", "both"),
trim.alpha = 0.25,
bootstrap = FALSE,
num.bootstrap = 1000,
correction.method = c("none", "correction.factor", "zero.removal", "zero.correction"),
correlation.method = c("pearson", "kendall", "spearman")
)
|
y |
a numeric vector of data values. |
group |
factor of the data. |
score |
weights to be used in testing an increasing/decreasing trend in
group variances, |
location |
the default option is |
tail |
the default option is |
trim.alpha |
the fraction (0 to 0.5) of observations to be trimmed from
each end of |
bootstrap |
a logical value identifying whether to implement bootstrap.
The default is |
num.bootstrap |
number of bootstrap samples to be drawn when the |
correction.method |
procedures to make the test more robust;
the default option is |
correlation.method |
measures of correlation; the default option is
|
The test statistic is based on
the classical Levene's procedure (using the group means),
the modified Brown–Forsythe Levene-type procedure (using the group medians),
or the modified Levene-type procedure (using the group trimmed means).
More robust versions of the test using the correction factor or structural zero
removal method are also available. Two options for calculating critical values,
namely, approximated and bootstrapped, are available.
By default, NA
s are omitted from the data.
A list of class "htest"
containing the following components:
statistic |
the value of the test statistic expressed in terms of correlation (Pearson, Kendall, or Spearman). |
p.value |
the p-value of the test. |
method |
type of test performed. |
data.name |
a character string giving the name of the data. |
t.statistic |
the value of the test statistic from Student's t-test. |
non.bootstrap.p.value |
the p-value of the test without bootstrap method. |
log.p.value |
the log of the p-value |
log.q.value |
the log of the (one minus the p-value). |
Kimihiro Noguchi, W. Wallace Hui, Yulia R. Gel, Joseph L. Gastwirth, Weiwen Miao
neuhauser.hothorn.test
, levene.test
,
lnested.test
, mma.test
, robust.mmm.test
1 2 3 4 5 6 7 8 9 10 | data(pot)
ltrend.test(pot[, "obs"], pot[, "type"], location = "median", tail = "left",
correction.method = "zero.correction")
## Bootstrap version of the test. The calculation may take up a few minutes
## depending on the number of bootstrap samples.
ltrend.test(pot[, "obs"], pot[, "type"], location = "median", tail = "left",
correction.method = "zero.correction",
bootstrap = TRUE, num.bootstrap = 500)
|
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