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# Computation of EWMA quantiles (variance monitoring) with pre-run uncertainty
sewma.q.prerun <- function(l, cl, cu, sigma, df1, df2, alpha, hs=1, sided="upper", r=40, qm=30, qm.sigma=30, truncate=1e-10) {
if ( l <= 0 | l > 1 ) stop("l (lambda) has to be between 0 and 1")
if ( cu<=0 ) stop("cu has to be positive")
if ( cl<0 ) stop("cl has to be non-negative")
if ( sided!="upper" & cl<1e-6 ) stop("cl is too small")
if ( sigma<=0 ) stop("sigma must be positive")
if ( df1<1 ) stop("df1 must be larger than or equal to 1")
if ( df2<1 ) stop("df2 must be larger than or equal to 1")
if ( alpha <= 0 | alpha >= 1) stop("quantile level alpha must be in (0,1)")
if ( hs<cl | hs>cu ) stop("wrong headstart hs")
ctyp <- pmatch(sided, c("upper","Rupper","two","Rlower")) - 1
if (is.na(ctyp)) stop("invalid ewma type")
if ( r<10 ) stop("r is too small")
if ( qm<5 ) stop("qm is too small")
if ( qm.sigma<4 ) stop("qm.sigma is too small")
if ( truncate < 0 | truncate >= 0.5 ) stop("wrong value for truncate (should follow 0 < truncate < 0.5)")
quant <- .C("sewma_q_prerun",
as.integer(ctyp), as.double(l), as.double(cl), as.double(cu),
as.double(alpha), as.double(hs), as.double(sigma),
as.integer(df1), as.integer(r), as.integer(qm),
as.integer(df2), as.integer(qm.sigma), as.double(truncate),
ans=double(length=1),PACKAGE="spc")$ans
names(quant) <- "q"
quant
}
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