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metric-1d – Metric based models in one dimension


metric-1d: metric based variance model functions in one dimension.

exp(x, init=NA, dist=NA)
expv(x, init=NA, dist=NA)
exph(x, init=NA, dist=NA)
gau(x, init=NA, dist=NA)
gauv(x, init=NA, dist=NA)
gauh(x, init=NA, dist=NA)
lvr(x, init=NA, dist=NA)
lvrv(x, init=NA, dist=NA)
lvrh(x, init=NA, dist=NA)
x An object in data.
init An optional vector of initial values (power parameters followed by variance parameters) with an optional names attribute from the set {P, U, F} specifying the boundary constraint as positive, unconstrained or fixed, respectively.
dist Optional numeric vector of coordinates (distances). If missing then the distances are obtained as unique(obj).

Includes one dimensional exponential, gaussian and linear variance power models (exp, gau, lvr).

asr_expv: Homogeneous variance form.
asr_exph: Heterogeneous variance form.
asr_gau: Gaussian power model.
asr_gauv: Gaussian power model, homogeneous variance form.
asr_gauh: Gaussian power model, heterogeneous variance form.
asr_lvr: Linear variance model.
asr_lvrv: Linear variance model, homogeneous variance form.
asr_lvrh: Linear variance model, heterogeneous variance form.
Updated on August 7, 2018

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