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python Programming Glossary: residualGetting standard errors on fitted parameters using the optimize.leastsq method in python http://stackoverflow.com/questions/14581358/getting-standard-errors-on-fitted-parameters-using-the-optimize-leastsq-method-i is the jacobian matrix and I must multiply this by the residual matrix to get my values. Unfortunately I am not a statistician.. Is this correct If not how would you go about getting the residual matrix to multiply the outputted Jacobian by to get my covariance.. The cov_x that leastsq outputs should be multiplied by the residual variance ie. s_sq func popt args 2 .sum len ydata len p0 pcov..
Curve fitting in Scipy with 3d data and parameters http://stackoverflow.com/questions/17934198/curve-fitting-in-scipy-with-3d-data-and-parameters y bs bm ba result red_dist blue_dist return result def residual p coords data import numpy as np model func3d p coords res model.flatten.. 1. bm 20. ba 2000. opt cov infodict mesg ier spopt.leastsq residual p_guess poiss_err H args coords maxfev 100000 full_output True.. the arguments here so you can do it as you like and pass a residual function however it's significantly easier to just use curve_fit..
Python Multiple Linear Regression using OLS code with specific data? http://stackoverflow.com/questions/7458391/python-multiple-linear-regression-using-ols-code-with-specific-data of freedom regression self.e self.y dot self.x self.b # residuals self.sse dot self.e self.e self.df_e # SSE self.se sqrt diagonal.. return stats.normaltest self.e def JB self Calculate residual skewness kurtosis and do the JB test for normality # Calculate.. kurtosis and do the JB test for normality # Calculate residual skewness and kurtosis skew stats.skew self.e kurtosis 3 stats.kurtosis..
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