theoLmoms.max.ostat(para=NULL, cdf=NULL, pdf=NULL, nmom=4, ...)
vec2par
or lmom2par
.expect.max.ostat
. Such arguments will likely tailor the integrations limits specific for the distribution in question.list
is returned.NULL
until trimming support is made.NULL
until trimming support is made.NULL
until trimming support is made.theoLmoms
, expect.max.ostat
para <- vec2par(c(40,20), type='nor')
theoLmoms.max.ostat(para=para, cdf=cdfnor, pdf=pdfnor)
# The Rice distribution is complex and tailoring of the integration
# limits is needed to effectively trapped errors, the limits for the
# Normal distribution above are infinite so no granular control is needed.
para <- vec2par(c(30,10), type="rice")
theoLmoms.max.ostat(para=para, cdf=cdfrice, pdf=pdfrice,
lower=0, upper=.Machine$double.max)
# The Normal distribution is used on the fly for the Rice for
# high signal to noise ratios (SNR=nu/alpha > some threshold). This
# application here will error out.
nu <- 30; alpha <- 0.5
para <- vec2par(c(nu,alpha), type="rice")
theoLmoms.max.ostat(para=para, cdf=cdfrice, pdf=pdfrice,
lower=0, upper=.Machine$double.max)
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