statistics

问题 I am doing a comparison of some alternate linear regression techniques. Clearly these will be bench-marked relative to OLS (Ordinary Least Squares). But I just want a pure OLS method, no preconditioning of the data to uncover ill-conditioning in the data as you find when you use regress() . I had hoped to simply use the classic (XX)^-1XY expression? However this would necessitate using the inv() function, but in the MATLAB guide page for inv() it recommends that you use mldivide when doing

问题 I am in the process of creating an django-powered (1.3) interface to a package that relies heavily in scipy.stats.stats (scipy version 0.9.0), called ovl . During early development phases, using djangos own development-server, this was no problem. After deployment using apache debian/2.2.9 and mod_wsgi 3.3, this causes a serious problem. Whatever view I'm trying to load in the browser, it starts loading, and keeps doing that for a good 5 minutes (until time-out) and a 500 page appears. Just

问题 I am trying to run a Augmented Dickey-Fuller test in statsmodels in Python, but I seem to be missing something. This is the code that I am trying: import numpy as np import statsmodels.tsa.stattools as ts x = np.array([1,2,3,4,3,4,2,3]) result = ts.adfuller(x) I get the following error: Traceback (most recent call last): File "C:\Users\Akavall\Desktop\Python\Stats_models\stats_models_test.py", line 12, in <module> result = ts.adfuller(x) File "C:\Python27\lib\site-packages\statsmodels-0.4.1

问题 I am trying to run a Augmented Dickey-Fuller test in statsmodels in Python, but I seem to be missing something. This is the code that I am trying: import numpy as np import statsmodels.tsa.stattools as ts x = np.array([1,2,3,4,3,4,2,3]) result = ts.adfuller(x) I get the following error: Traceback (most recent call last): File "C:\Users\Akavall\Desktop\Python\Stats_models\stats_models_test.py", line 12, in <module> result = ts.adfuller(x) File "C:\Python27\lib\site-packages\statsmodels-0.4.1

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 6 years ago . I want to make stats for my website. One thing I want to do is to know how many people bookmark my website. What's the best way to do that without a survey? 回答1: Your best bet is to have a Javascript "Bookmark us" link that bookmarks the site and makes an AJAX call to a backend script to store info about a new

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 6 years ago . I want to make stats for my website. One thing I want to do is to know how many people bookmark my website. What's the best way to do that without a survey? 回答1: Your best bet is to have a Javascript "Bookmark us" link that bookmarks the site and makes an AJAX call to a backend script to store info about a new

问题 The R^2 value returned by scikit learn ( metrics.r2_score() ) can be negative. The docs say: "Unlike most other scores, R² score may be negative (it need not actually be the square of a quantity R)." However the wikipedia article on R^2 mentions no R (not squared) quantity. Perhaps it uses absolute differences instead of square differences. I really have no idea 回答1: The R^2 in scikit learn is essentially the same as what is described in the wikipedia article on the coefficient of

问题 I have the following list of values: x = [-0.04124324405924407, 0, 0.005249724476788287, 0.03599351958245578, -0.00252785423151014, 0.01007584102031178, -0.002510349639322063,...] and I want to calculate the empirical density function, so I think I need to calculate the empirical cumulative distribution function and I've used this code: counts = np.asarray(np.bincount(x), dtype=float) cdf = counts.cumsum() / counts.sum() and then I calculate this value: print cdf[0.01007584102031178] and I

问题 Code where I would like to do 2x2 barcharts side-by-side such that the y-axis max value would be the same in all and common ylabel common xlabel common legends common title each barchart with their own subtitle separator line between each barchart like in Fig. 2 Code # Wanted output 2x2 barchart where top column Ite. 1 and Ite. 2 and row-names female and male # http://www.magesblog.com/2012/12/changing-colours-and-legends-in-lattice.html require("lattice") f<-function(x) as.double(as

问题 Code where I would like to do 2x2 barcharts side-by-side such that the y-axis max value would be the same in all and common ylabel common xlabel common legends common title each barchart with their own subtitle separator line between each barchart like in Fig. 2 Code # Wanted output 2x2 barchart where top column Ite. 1 and Ite. 2 and row-names female and male # http://www.magesblog.com/2012/12/changing-colours-and-legends-in-lattice.html require("lattice") f<-function(x) as.double(as