Create a List of lm Objects with Common Regression Model
USAGE: 
lmList(formula, data, cluster)
REQUIRED ARGUMENTS:
formula:
a linear formula object, with the response on the left of a ~ operator and the terms, separated by + operators, on the right.
data:
a data frame in which to interpret the variables named in formula and cluster.
cluster:
an expression or formula object, specifying the partitioning of the data according to which different lm() fits should be performed. If cluster is given as a formula, it should have no left side to the ~expression.
VALUE:
a list of lm objects with as many components as the number of clusters defined by cluster. Generic functions such as coef(), pairs(), summary(), fixed.effects(), random.effects(), and lme() have methods that can be applied to an lmList object.
SEE ALSO:
lm , lme.lmList .
EXAMPLES: 
Ovary.lmList <- lmList(follicles ~ sin(2 * pi * Time) +
                       cos(2 * pi * Time),
                       data = Ovary, cluster = ~ Mare)


Ovary.lmList


# Returns the following:
  $"1":
  Call:
  lm(formula = formula, data = dat)


  Coefficients:
   (Intercept) sin(2 * pi * Time) cos(2 * pi * Time)
      15.71444         -0.7805058           -1.81328


  Degrees of freedom: 29 total; 26 residual
  Residual standard error: 2.853338


  . . .


  $"11":
  Call:
  lm(formula = formula, data = dat)


  Coefficients:
   (Intercept) sin(2 * pi * Time) cos(2 * pi * Time)
      9.451102          -1.269141          -1.787266


  Degrees of freedom: 27 total; 24 residual
  Residual standard error: 2.261535