A great deal of the statistical literature deals with a single sample coming from a distribution, univariate or multivariate, and the problem is to identify the distribution or parts thereof by an array of estimation and testing procedures. As such, this practice neglects to bring in information from other sources which could improve the desired inference. An approach which fuses information from many sources will be presented and applied in various statistical problems, including time series forecasting.