ABSTRACT
Least squares approximation to a set of data points is a very handy tool for expressing coefficients. It should be remembered that only those equations of the curves that can be easily linearized using known techniques will be considered. The trigonometric function can have one or more terms in sine or cosine or tangent. These are generally useful when the input data vary according to one of them. The first one is to fit the data on moisture content and time to a suitable linear or nonlinear regression and later tit the values of each of the coefficients of such an equation and temperature and relative humidity to a multilinear. The second method is to fit the data on moisture, time, temperature and relative humidity to a multilinear regression. The FORTRAN source code of the main calling program to do the above trigonometric regression.
