Nothing
powerlaw_n_params = function() {
2
}
powerlaw_param_names = function() {
c("sigma2", "d")
}
powerlaw_v_tran = function(theta) {
theta_t = rep(0, length(theta))
theta_t[1] = transfo_exp(theta[1]) # sigma2
theta_t[2] = transfo_logit(theta[2])*0.4999 # fgn d (from 0 to 0.5)
return(theta_t)
}
powerlaw_v_tran_inv = function(theta) {
theta_t = rep(0, length(theta))
theta_t[1] = inv_transfo_exp(theta[1]) # sigma2
theta_t[2] = inv_transfo_logit(theta[2]/0.4999) # fgn d (from 0 to 0.5)
return(theta_t)
}
powerlaw_theo_wv = function(theta, scales) {
autocovariance_to_wv(powerlaw_autocovariance(theta, tail(scales,1)), scales)
}
# powerlaw_autocovariance = function(theta, n) {
# sigma2 = theta[1]
# d = theta[2]
#
# acf = rep(0, n)
# acf[1] = gamma(1.0-2.0*d)/gamma(1.0-d)^2*sigma2
#
# for (j in 1:(n-1)) {
# acf[j+1] = (d+j-1.0)*acf[j]/(j-d);
# }
#
# acf
# }
powerlaw_theta_to_exp = function(theta) {
bquote( PowerLaw(sigma^2 == .(sprintf('%.2f', theta[1])), d == .(sprintf('%.2f', theta[2])) ) )
}
powerlaw_pick_params_hector = function(json) {
params = c(
json$driving_noise^2 * json$NoiseModel$Powerlaw$fraction,
json$NoiseModel$Powerlaw$d
)
}
powerlaw_name_hector = function() {
"Powerlaw"
}
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