hfigt {ig} | R Documentation |
Hazard function (hf) or failure rate for the IGTD with mean parameter mu,
scale parameter lambda and associated kernel g
.
hfigt(x, mu = 1.0, lambda = 1.0, nu = 1.0, kernel = "normal")
x |
Vector of observations. |
mu |
Mean. |
lambda |
Scale parameter. |
nu |
Shape parameter corresponding to the degrees of freedom of the t distribution. In the case of the Laplace, logistic, normal kernels, nu can be fixed at the value 1.0 since this parameter is not involved in these kernels. |
kernel |
Kernel of the pdf of the associated symmetrical distribution
by means of which the IGTD is obtained. The kernels:
"laplace" , "logistic" , "normal" and
"t" are available. |
The IGTD has hf given by
h_T(t) = frac{f_Z(a_{t}) , frac{sqrt{λ}}{sqrt{t^{3}}}} {F_Z(-a_t) - int^{infty}_{b_t} c , g(u^2 - frac{4 , λ}{μ}) mbox{footnotesize d}u}.
hfig()
gives the hf of an IGTD.
Víctor Leiva <victor.leiva@uv.cl; victor.leiva@yahoo.com>,
Hugo Hernández <hugo.hernandez.p@gmail.com> and
Antonio Sanhueza <asanhueza@ufro.cl>.
Sanhueza, A., Leiva, V., Balakrishnan, N. (2008). A new class of inverse Gaussian type distributions. Metrika (in press).
## Computes the hf of the IGTD with normal kernel for a vector x with mu = 1.0, ## lambda = 1.0 x <- seq(0.01, 4, by = 0.01) hx <- hfigt(x, mu = 1.0, lambda = 1.0, nu = 1.0, kernel = "normal") print(hx) ## At the end there is the graph of this pdf plot(x, hx, main = "hf of the IGTD (classical case)", ylab = "h(x)")