Wald,likelihood ratio,and Lagrange multiplier tests as an F test

This expository note contains, in the case of a multiple regression model, a derivation of the Wald, Lagrange, and Likelihood Ratio tests as a function of the small sample F test. This also allows us to readily establish the well-known small sample inequalities among the first three large sample tests.     

Analytical analysis of a generic assembly system

The assembly of components is a key element in manufacturing facilities. Nevertheless, literature analyzing the dynamic behavior remains scarce. The paper narrows this gap by studying a generic first-come first-serve assembly system, consisting of two generally distributed component input streams. The field of probability theory serves as a means to derive good approximations for the waiting time of the components to form a kit and the inter-arrival time of the kits at the assembly station. Apart from providing insight in generally accepted managerial principles, this analysis also constitutes a required step in obtaining the performance of an open queuing network including assemblies.     

Robust estimation of ARIMA models

The paper discusses methods of estimating univariate ARIMA models with outliers. The approach calls for a state vector representation of a time-series model, on which we can then operate on using the Kalman filter. One of the additional advantages of Kalman filter operating on the state vector representation is that the method and code could easily be adapted to be applicable to the ARIMA model with missing observations. The paper investigates ways to calculate robust initial estimation of the parameters of the ARIMA model. The method proposed is based on the results obtained by R.D. Martin (1980).