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 Description:
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   This is the main function to perform Functional Variance Process Analysis
 
 Includes the following steps:
 
 1) PACE Estimation for the original processes Y.
 
 2) Calculation of the raw residual process from step 1.
 
 3) PACE Estimation for the functional variance processes.

 See reference:  M\"uller, H.G., Stadtm\"uller, U., Yao, F. (2006). Functional variance processes. 
                 Journal of the American Statistical Association 101, 1007-1018. 
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 Usage:
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     [rr,sigma,yy] = FVP(y,t,p)
 
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Input: 
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      y:          1*n cell array, y{i} is the vector of measurements for the ith subject,
                  i=1,...,n.
      t:          1*n cell array, t{i} is the vector of time points for the ith subject on which
                  corresponding measurements y{i} are taken, i=1,...,n.
      p:          a struct obtained from setOptions.m sets the rest of arguments for PCA.m
                  ex:
                  >> p = setOptions();
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Output:  
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     rr:          a cell array that contains all returned values from PCA.m for the functional 
                  variance processes.
  sigma:          the variance estimator of the functional variance process.
     yy:          a cell array that contains all returned values from PCA.m for the original 
                  functional processes.
      

   To see the names for rr, type names(rr)
   To get individual value back, type getVal(rr,varname)
   To see an example, check with example.m
   See also FPCA, PCA, example, names

 Note: Squared residuals are adjusted by adding the 10th percentile of  the pooled sample before taking log.