Abstract:
Statistically, change point is the location or the time point such that observations
follow one distribution up to the point and then another afterwards. Change point
problems are encountered in our daily life and in disciplines such as economics,
finance, medicine, geology, literature among others. In this paper, the change point
in binomial observations whose the mean is dependent on explanatory variables is
estimated. The maximum likelihood method was used to estimate the change point
while the conditional means were estimated using the artificial neural network
The consistency and asymptotic normality of neural network parameter estimates
was also proved. We used simulated data to estimate the change point and also
estimated the LD50 for the Bliss beetles data.
