dAR1 | R Documentation |
Density for the AR-1 model.
dAR1(x, drift = 0, var.error = 1, ARcoef1 = 0.0,
type.likelihood = c("exact", "conditional"), log = FALSE)
x |
vector of quantiles. |
drift |
the scaled mean (also known as the drift parameter),
|
log |
Logical.
If |
type.likelihood , var.error , ARcoef1 |
See |
Most of the background to this function is given
in AR1
.
All the arguments are converted into matrices, and then
all their dimensions are obtained. They are then coerced
into the same size: the number of rows is the maximum
of all the single rows, and ditto for the number of columns.
dAR1
gives the density.
T. W. Yee and Victor Miranda
AR1
.
## Not run:
nn <- 100; set.seed(1)
tdata <- data.frame(index = 1:nn,
TS1 = arima.sim(nn, model = list(ar = -0.50),
sd = exp(1)))
fit1 <- vglm(TS1 ~ 1, AR1, data = tdata, trace = TRUE)
rhobitlink(-0.5)
coef(fit1, matrix = TRUE)
(Cfit1 <- Coef(fit1))
summary(fit1) # SEs are useful to know
logLik(fit1)
sum(dAR1(depvar(fit1), drift = Cfit1[1], var.error = (Cfit1[2])^2,
ARcoef1 = Cfit1[3], log = TRUE))
fit2 <- vglm(TS1 ~ 1, AR1(type.likelihood = "cond"), data = tdata, trace = TRUE)
(Cfit2 <- Coef(fit2)) # Okay for intercept-only models
logLik(fit2)
head(keep <- dAR1(depvar(fit2), drift = Cfit2[1], var.error = (Cfit2[2])^2,
ARcoef1 = Cfit2[3], type.likelihood = "cond", log = TRUE))
sum(keep[-1])
## End(Not run)
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