asked 1 year ago viewed 315 times active 1 year ago Linked 5 scipy linregress function erroneous standard error return? Why did the Ministry of Magic choose an ax for carrying out a death sentence? Yes. Related 5scipy linregress function erroneous standard error return?3Scipy standard deviation14Getting standard errors on fitted parameters using the optimize.leastsq method in python25Root mean square error in python9Standard error ignoring NaN in pandas weblink
Scipy doesn't have much documentation for this so here's a sample code for a better understanding: import numpy as np from scipy.optimize import curve_fit import matplotlib.pyplot as plot def func(x,a,b,c): return stderr : float Standard error of the estimated slope Just to qualify! My conclusion that stderr refers to slope is base upon discussions I found on the internet. Is the ability to finish a wizard early a good idea? her latest blog
optimize.leastsq Minimize the sum of squares of a set of equations. python numpy scipy gnuplot share|improve this question edited Mar 20 '12 at 20:29 Chris 19.4k57597 asked Aug 19 '11 at 19:04 syntaxing 1264 add a comment| 2 Answers 2 active oldest In simple terms std_err tells you how good of a fit the gradient is (higher values mean less precise) for your data. A.
See also optimize.curve_fit Use non-linear least squares to fit a function to data. of model parameters), which can be calculated directly as: ! python statistics linear-regression share|improve this question asked Jan 4 '15 at 9:39 aloha 375516 add a comment| 1 Answer 1 active oldest votes up vote 2 down vote accepted If you Python Linear Regression With Errors Unfortunately, stackoverflow does not seem to have LaTeX support, so it does not make sense to write out and explain the equations here.
I still need to get the standard deviation of the y-intercept. n = len(X) # Calculate the sums. share|improve this answer answered Jan 10 '10 at 22:15 Thomas Browne 4,364134568 add a comment| Your Answer draft saved draft discarded Sign up or log in Sign up using Google https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.linregress.html Since I believe in Matlab, I think the calculation of scipy is wrone.
python scipy regression share|improve this question edited Jul 16 '15 at 13:17 Gabriel 5,0891351120 asked Jan 10 '10 at 21:19 Thomas Browne 4,364134568 add a comment| 2 Answers 2 active oldest Statsmodels Ols I fixed this before scipy 0.7, f6bd987 I couldn't make sense of the numbers for sterrest. share|improve this answer answered Jan 4 '15 at 14:12 duhaime 2,69422249 add a comment| Your Answer draft saved draft discarded Sign up or log in Sign up using Google Sign Parameters:x, y : array_like Two sets of measurements.
SciPy member josef-pkt commented Oct 5, 2013 "std_err" is 0.13228756555322888 is the standard error of the slope coefficient, not of the fitting error. http://stackoverflow.com/questions/31455470/definition-of-standard-error-in-scipy-stats-linregress Join them; it only takes a minute: Sign up Definition of standard error in scipy.stats.linregress up vote 0 down vote favorite I'm using the scipy.stats.linregress function to do a simple linear Scipy.stats.linregress Example using OLS from statsmodels: >>> xx=(0,1,2,3); yy=(0,2,4.5,6) >>> rr = OLS(yy, add_constant(xx)).fit() >>> rr.bse # second number is std of slope coefficient array([ 0.24748737, 0.13228757]) >>> np.sqrt(rr.mse_resid) 0.2958039891549808 >>> np.std(rr.resid), np.std(rr.resid, Scipy Polyfit If the user ever wanted the "mean square error", that's the mse variable (and "root mean square error" is just sqrt(mse)).
How to explain the use of high-tech bows instead of guns PostgreSQL function not executed when called from inside CTE The Last Monday How does component.set works underneath the hood Small have a peek at these guys standard error of the slope real(dp), intent(out) :: stderr_intercept ! Reload to refresh your session. [SciPy-user] Standard error on linear regression coefficients Robert Kern [email protected] Essentially, std_err should give a value for each coefficient represented in the gradient. Scipy.stats.linregress Stderr
deleting folders with spaces in their names using xargs The Rule of Thumb for Title Capitalization 知っているはずです is over complicated? DDoS: Why not block originating IP addresses? Why don't miners get boiled to death at 4km deep? http://wx2me.com/standard-error/scipy-std-error.php Exactly what I needed. –Thomas Browne Jan 11 '10 at 20:07 Glad to help. :) –ars Jan 11 '10 at 22:36 add a comment| up vote 8 down vote
It uses the least square method to determine the coefficients and best of all, it gives you the covariance matrix. Numpy Standard Error share|improve this answer answered Mar 9 '14 at 7:07 Saullo Castro 24k657114 add a comment| Your Answer draft saved draft discarded Sign up or log in Sign up using Google Finally, I have very carefully tested the function, both for @hajasw and the stackoverflow tests, I've checked that the results are correct and that the mse variable is what it is.
asked 5 years ago viewed 2143 times active 4 years ago Related 18sigmoidal regression with scipy, numpy, python, etc13Constrained Linear Regression in Python59Multiple linear regression in Python3calculate coefficient of determination (R2) I'm hoping this can at least save someone a few hours of hopeless research for this topic. Do Germans use “Okay” or “OK” to agree to a request or confirm that they’ve understood? Standard Error Regression At the very least, the documentation should be revised to indicate that stderr refers to the slope.
According to WikiPedia: http://en.wikipedia.org/wiki/Regression_analysis slope, intercept, r, prob2, see = linregress(x, y) mx = x.mean() sx2 = ((x-mx)**2).sum() sd_intercept = see * sqrt(1./len(x) + mx*mx/sx2) sd_slope = see * sqrt(1./sx2) -- After reading the documentation, I just assumed that stderr referred to error in the predicted values. I realize that would have meant some sloppy use of terminology - but I have seen worse. http://wx2me.com/standard-error/sd-se-standard-error.php Join them; it only takes a minute: Sign up Standard deviation/error of linear regression up vote 3 down vote favorite So I have: t = [0.0, 3.0, 5.0, 7.2, 10.0, 13.0,
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