# Package solutions

- Class Summary
  Class | Description
  --- | ---
  S1Anova | Performing an analysis of variance with crossed classification on simulated data
  S1Distrib | Convolution of uniform distributions
  S1Lsq | Data corresponding to 2nd degree polynomial fitted by 1st degree
  S1MaxLike | Maximum-likelihood estimate of mean life from few decays
  S1Min | Use of various minimization methods; first approximation found by Monte-Carlo method
  S1Random | Creation of random numbers distributed according to a Breit-Wigner distribution
  S1Reg | Polynomial regression on created data
  S1TimSer | Creating data modelling a power law and performing a time series analysis on them
  S2Anova | Performing an analysis of variance with nested classification on simulated data
  S2Distrib | Convolution of uniform distribution with Gaussian
  S2Lsq | Data fitted to power law (linear case)
  S2MaxLike | Distribution of the sample correlation coefficient
  S2Min | Fitting a Breit-Wigner function to small sample and determining errors of parameters by MinCov
  S2Random | Creation of random numbers distributed according to a triangular distribution
  S2Reg | Polynomial regression on created data.
  S2TimSer | Creating data modelling a sine, a step, or a saw-toot function and performing a time series analysis on them
  S3Lsq | Data fitted to power law (nonlinear case)
  S3Random | Points fluctuating about a straight line, having errors of different sizes
  S4Lsq | Data generated according to a Breit-Wigner function are fitted to Breit-Wigner or to Gaussian
  S5Lsq | Data following a Breit-Wigner function are fitted to BW or Gaussian; asym. errors and confid. region shown
  S6Lsq | Fit of a Breit-Wigner function to a histogram
  S7Lsq | Fitting a circle to data points