Conditional least-squares estimate for Poisson INAR(1) models {Rfast2} | R Documentation |
Conditional least-squares estimate for Poisson INAR(1) models
Description
Conditional least-squares estimate for Poisson INAR(1) models.
Usage
pinar1(x, unbiased = FALSE)
colpinar1(x, unbiased = FALSE)
Arguments
x |
Either a numerical vector or a matrix, depending on the function. |
unbiased |
If you want the unbiased estimation select TRUE. |
Details
The function computes the constant and slope coefficients of the Poisson Integer Autoregressive of order 1 (Poisson INAR(1)) model using the conditional least-squares method.
Value
For pinar1() a vector with two values, the \lambda
coefficient (constant)
and the \alpha
coefficient (slope). See references for more information.
For the colpinar1() a matrix with two columns, the \lambda
coefficient
(constant) and the \alpha
coefficient (slope) for each variable (column of x).
Author(s)
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
References
M. Bourguignon and K.L.P. Vasconcellos (2015). Improved estimation for Poisson INAR(1) models. Journal of Statistical Computation and Simulation, 85(12): 2425-2441
See Also
Examples
x <- rpois(200, 10)
pinar1(x)