INNER CODE UNIT · Python

LSfit

mszell/geospatialdatascience · unit11_mobilityindividual/stats_utils.py:220

def LSfit(function, parameters, y, x):
    """
    *** ATTENTION! ***
    *** _x_ and _y_ MUST be NUMPY arrays !!! ***
    *** and use NUMPY FUNCTIONS, e.g. np.exp() and not math.exp() ***

    _function_    ->   Used to calculate the sum of the squares:
                         min   sum( (y - function(x, parameters))**2 )
                       {params}

    _parameters_  ->   List of elements of the Class "Parameter"
    _y_           ->   List of observations:  [ y0, y1, ... ]
    _x_           ->   List of variables:     [ [x0,z0], [x1,z1], ... ]

    Then _function_ must be function of xi=x[0] and zi=x[1]:
        def f(x): return x[0] *  x[1] / mu()

        # Gaussian

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