seCor: Compute the standard error accounting for empirical...
In lognorm: Functions for the Lognormal Distribution

Description Usage Arguments Details Value

Compute the standard error accounting for empirical autocorrelations

seCor(
  x,
  effCor = if (missing(effCov)) computeEffectiveAutoCorr(x) else effCov/var(x, na.rm =
    TRUE),
  na.rm = FALSE,
  effCov,
  nEff = computeEffectiveNumObs(x, effCor, na.rm = na.rm)
)

`x`	numeric vector
`effCor`	numeric vector of effective correlation components first entry at zero lag equals one. See `computeEffectiveAutoCorr`
`na.rm`	logical. Should missing values be removed?
`effCov`	alternative to specifying effCor: numeric vector of effective covariance components first entry is the variance. See `computeEffectiveAutoCorr`
`nEff`	possibility to specify precomputed number of effective observations for speedup.

The default uses empirical autocorrelation estimates from the supplied data up to first negative component. For short series of x it is strongly recommended to to provide effCov that was estimated on a longer time series.

numeric scalar of standard error of the mean of x

lognorm documentation built on Nov. 22, 2021, 1:07 a.m.