SciPy 0.6.0 API Documentation Generated by Endo, 2007-10-17

Variables

• exponential

  exponential = Model(_exp_fcn, fjacd = _exp_fjd, fjacb = _exp_fjb, estimate = _exp_est, meta = { Const('name') : Const('Exponential'), Const('equ') : Const('y= B_0 + exp(B_1 * x)'), Const('TeXequ') : Const('$y=\\beta_0 + e^{\\beta_1 x}$') })
  
  

• multilinear

  multilinear = Model(_lin_fcn, fjacb = _lin_fjb, fjacd = _lin_fjd, estimate = _lin_est, meta = { Const('name') : Const('Arbitrary-dimensional Linear'), Const('equ') : Const('y = B_0 + Sum[i=1..m, B_i * x_i]'), Const('TeXequ') : Const('$y=\\beta_0 + \\sum_{i=1}^m \\beta_i x_i$') })
  
  

• quadratic

  quadratic = Model(_quadratic, fjacd = _quad_fjd, fjacb = _quad_fjb, estimate = _quad_est, meta = { Const('name') : Const('Quadratic'), Const('equ') : Const('y = B_0*x**2 + B_1*x + B_2'), Const('TeXequ') : Const('$y = \\beta_0 x^2 + \\beta_1 x + \\beta_2') })
  
  

• unilinear

  unilinear = Model(_unilin, fjacd = _unilin_fjd, fjacb = _unilin_fjb, estimate = _unilin_est, meta = { Const('name') : Const('Univariate Linear'), Const('equ') : Const('y = B_0 * x + B_1'), Const('TeXequ') : Const('$y = \\beta_0 x + \\beta_1$') })
  
  

Function summary

• polynomial(order)

Functions

• polynomial(order)

  Factory function for a general polynomial model.

  Parameters

  order : int or sequence

  If an integer, it becomes the order of the polynomial to fit. If a sequence of numbers, then these are the explicit powers in the polynomial. A constant term (power 0) is always included, so don't include 0. Thus, polynomial(n) is equivalent to polynomial(range(1, n+1)).

  Returns

  model : Model instance

Imported Names