WE are Carlos David Pastran and Elimar Hernandez,we do not speak english,
we do speak spanish.
We are Research student.
Nuestra duda es obtener un analisis muy detallado, una explicacion con
ecuaciones matematicas y estadisticas acerca de todos los parametros del
modelo de intervencion.
Aqui se da una respuesta que ustedes le enviaron a
jmckinlay@fish.wa.gov.au, que es:
One way to introduce gradual changes is to use models such as
y(t) = c +| a y(t-1) + bx(t)+ e(t)
where x(t) is the indicator variable. Suppose the intervention occurs
at time T. Prior to the intervention the mean of the process is
c/(1-a). At time T+j , i.e. j observations after the intervention add
(a^j)*b to the mean, so that the post intervention mean converges
geometrically to (c+b)/(1-a). The easy way of fitting this model is to set
the
regression variables (xreg) in the arima function to be the x(t) and
lagged y(t-1), i.e. simply regress y(t) on x(t) and y(t-1). This
assumes that the residuals are uncorrelated, but upon examining the acf
and pacf of the residuals you can often identify an appropriate model
for the noise term that can be incorporated into the arima model. Of
course there is the problem of identifying the nature of the
intervention model in the first place - if you expect intervention
effects to converge geometrically to a new level then the above model
Se le agradece una pronta respuesta
may be ok.
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