1. In a computer system having a memory and storage medium, a method for estimation of changes in key performance indicator distribution, the method comprising: establishing a state-space model in the computer memory, the model for handling measurement errors and modelling errors as noise, wherein time-varying indices have historical data and a correlation with key performance indicators; adaptively estimating parameters related to the time varying indices, and obtaining residuals from the adaptive estimate of the parameters; estimating a probability distribution in order to generate random numbers from the probability distribution; generating random numbers related to the estimated probability distribution, thereby enabling prediction of future indicator distributions through a Sequential Monte Carlo method; providing models to input key performance indicator intensity levels for a scenario level and to predict future values for a plurality of scenarios as point estimates; and distributing and synthesizing the point estimation results for the plurality of scenarios based on key performance indicator estimated probability distributions.