This thesis focuses on the analysis of nonstationary processes with linearly time vary-ing periodic behavior. First we develop LM-stationary processes for analyzing time series data with linearly compacting periodic behavior. Spectral analysis using this method shows better performance than that using the Wigner-Ville time frequency distribution. The LM-stationary forecasts produce better results than autoregressive forecasts applied directly to time...