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Questions tagged [scipy]

SciPy is a Python-based ecosystem of open-source software for mathematics, science, and engineering.

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0answers
45 views

Can't understand the Beta distribution as described in this paper

I'm reading through the following paper (1). On page 2, section 2.1, there's a description of the selection of a beta distribution used: Since both the choice of s and the strategy for handling the ...
0
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1answer
27 views

Fixing the maximum distance within a cluster

I am trying to cluster geographical locations in such a way that all the locations inside each cluster are at max within 25 miles of each other. For this, I am using Agglomerative clustering. I am ...
3
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1answer
245 views

Why is computing ridge regression with a Cholesky decomposition much quicker than using SVD?

By my understanding, for a matrix with n samples and p features: Ridge regression using Cholesky decomposition takes O(p^3) time Ridge regression using SVD takes O(p^3) time Computing SVD when only ...
2
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0answers
26 views

Why is it much quicker to compute ridge regression than regular linear regression?

By my understanding, for a matrix with n samples and p features: Ridge regression using cholesky takes O(p^3) time Ordinary linear regression takes O(p^3) time Singular value decomposition if u, v ...
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0answers
7 views

How to stop fmin_slqsp from converging to local minimum?

I want to run linear regression with inequality constraints and non-negative coefficients. My data looks roughly like this: ...
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0answers
34 views

Proper way to plot confidence interval under normal distribution curve?

I write a small program which calculates a confidence interval for a given norm value. The output is then visualized by plotting the confidence interval and the corresponding hypothetical norm value ...
0
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0answers
21 views

Numerical approximation of sandwich estimator

I have found the MLE of a model using scipy.optimize.minimize with the BFGS algorithm. As is commonly done, I intend to estimate the variance from $$ Var(\theta_0) ...
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1answer
20 views
1
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1answer
18 views

How to estimate the leafsize of the kd-tree?

The kd-tree implementation proposed by the scipy python libray asks for the value of the leafsize parameter that is to say the maximum number of points a node can hold. It is by default set to 10. ...
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0answers
10 views

Constructing an appropriate null hypothesis?

I have a collection of 20 2D surfaces embedded in 3D. The mean curvature of each surface has been sampled. The number of samples per surface varies from ~700,000 to ~20,000,000. The choice of ...
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0answers
79 views

Calculating P-value for multivariate normal distributions?

I'm given a set of 500 ($\sigma_i, \mu_i$) that define a 500-dimensional multivariate normal distribution, where each dimension is effectively independent from all the others. Given a 500-...
2
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1answer
325 views

How does scipy calculate the binomial CDF so fast?

I ran scipy.stats.binom.cdf(500006, 1000000, 0.5) and it took less than a milisecond. This is crazy as binomial CDF involves summing up a bunch of binomial coefficients. What approximation algorithm ...
0
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1answer
77 views

How to perform batch training using L-BFGS?

I want to train a neural network for regression. The neural network is actually composed of 4 separate child neural networks, each child neural network has a layer structure of ...
1
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3answers
59 views

How to calculate the p-value of a test, that checked for a binary property?

16081 subjects were randomly assigned into two groups: test group: 7916 subjects control group: 8165 subjects Only the test group was exposed to something. During the test period 10 subjects of ...
0
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1answer
101 views

Normal distribution test ( D'Agostino and Pearson's) in Scipy - results don't make sense

I want to test if an array of numbers is approximately normally distributed. ...
1
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0answers
15 views

3 Layer neural network (feedforward and backpropagation) - Desired error not necessarily achieved due to precision loss

I am trying to implement a 3 layer neural network with feedforward and backpropagation. I have tested my cost function and it is working fine. My gradient function also seems ok. but when I try to ...
0
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0answers
84 views

Calculate horizontal asymptote for data set with python

I have a data set comprised of X files. Each file contains Y 60-bit binary numbers that are not random but I don't have access to the rules that would tell me the allowed bit patterns and allow me to ...
0
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1answer
28 views

Remove individual points and find slope

I am trying to delete one pair of x and y coordinates from a set of 10 data points and get the slope for the other 9 points. How do I go about this issue? Attached herewith is an image of what I am ...
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0answers
195 views

Update R2 and slope by removing outliers-python [closed]

I am using the following code to find out Linregress parameters: ...
0
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1answer
235 views

Statsmodels' Negative Binomial: after .fit_regularized(), how to turn PMF into PPF to get the discrete values?

I used the package statsmodels to fit a Negative Binomial to my data. This data contains ~1500 samples with 21 covariates. Since I have overdispersion in my data ...
0
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1answer
16 views

Can findings based on low values be considered valid?

Lets say i do have a TimeSeries with N > 300 but values like [0, 1, 2, 1, 2, 0, 2, ...] representing the visitors count of a website per day. Since there are only few visitors and each of them can be ...
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0answers
59 views

Problem with U Mann Whitney test in scipy for nominal values

When I am using scipy.stats.mannwhitneyu sometimes I got this error: TypeError: '<' not supported between instances of 'int' and 'str' Should not it work? I have noticed that scipy.stats....
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0answers
75 views

Periodogram interpretaion to get main cycles for time serie

I try to use the periodogram in order to get main cycle on my time series. My time series is a the result of measure every hour of one variable related with the atmosphere. So in one day I have 24 ...
1
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1answer
326 views

How to know if a parameter is statistically significant in a “curve_fit” estimation? [closed]

I use curve_fit from scipy to estimate parameter values from a specific function. ...
0
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1answer
82 views

nmf in scipy returns components with all zero weights

I'm trying to understand whether this behavior is a bug or a feature. Essentially, I have a dataset of ten thousand short pieces of text. I have used the CountVectorizer function to turn this into a ...
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0answers
22 views

Mode of function kstest in module scipy.stats.stats

In the function kstest in module scipy.stats.stats, there are two options for the mode, described in the help file: ...
2
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1answer
242 views

Gaussian Mixture Model

with the following code I fit a Gaussian Mixture Model to arbitrarily created data. The code is working. The only thing I encounter is that during the calculation of the multivariate_normal I ...
0
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1answer
441 views

Bandwidth parameters in multivariate KDE using scipy.stats.gaussian_kde

I am working on a project which involves implementing in Python two different density estimation functions over multivariate data; one using N-d histograms and the other using kernel density ...
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1answer
98 views
0
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1answer
141 views

Interpreting p value in SciPy Welch's T-Test [duplicate]

Can someone help me understand the meaning of the p-value of the Whelch's T Test in SciPy? test = stats.ttest_ind(x, y, equal_var=False) gives me ...
2
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1answer
2k views

How to Compare the Data Distribution of 2 datasets?

I'm having trouble to understand how to compare 2 sets of data by their distribution . For Example, how can I understand that column X100 has the same distribution as column Y1? Also, is there a ...
1
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2answers
124 views

Normality test giving confusing results

So I was transforming data for machine learning purposes and checking whether I should use the data or log-transform it. In addition to creating histograms I decided to test for normality using ...
0
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0answers
275 views

Tuning skopt to minimise correctly

I have a problem where I need to fit a pair of parameters in a model to best fit observed data for hundreds of instances. I need to determine these parameters to high accuracy, rather than just ...
2
votes
1answer
459 views

Understanding hypothesis testing (Kruskal Wallis, Mann-Whitney) when there are tied values

tldr: In Python's Scipy stats modules, the kruskal and mannwhitneyu functions will both raise an error if called with only ...
2
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0answers
71 views

Fitting two parallel lines with mutually excluding samples

I have a set of (slightly noisy) data taken from two (or more) curves, but taken either from one or the other curve. As an example, consider this code (in reality, data is noisier, especially in how ...
1
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2answers
285 views

Time Series: use of Box-Cox to reduce the “noise”

I am researching the best method to use with time series. FBprophet (Python) seems like a strong option. To prepare time series for Prophet I am thinking about using boxcox and inv_boxcox at the end ...
0
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0answers
125 views

scipy.optimize.minimize How to manage different units?

I am wondering how spicy.optimize.minimize manages different units in the searched vector. My vector is [x,y,z,yaw,pitch,roll]. The first three are translations in <...
1
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0answers
374 views

How to consider “pratt” zero method in Wilcoxon Test of R, which is available in Python Scipy?

I have a dataset of two columns which represent rank data. These ranks are ranged from 1, 2, and 3. To test the difference in medians between these two columns, I am considering the Wilcoxon rank-sum ...
1
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2answers
154 views

Database-friendly random projections with Numpy

In his well known paper [1], Achlioptas showed that Random Projections could be performed with a sparse projection matrix, whose nonzero entries are either $1$ or $-1$. I have noticed that scikit-...
1
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0answers
82 views

Working between sklearn and scipy for convex optimization [closed]

I have a method for solving convex programs using an alternative method of iterative procedures and would like to compare this to current solvers methods. My approach relies upon randomly projecting ...
0
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0answers
114 views

Methods for selecting the required n_components for TruncatedSVD?

Methods for selecting the required n_components for TruncatedSVD? I found this (https://chrisalbon.com/machine_learning/feature_engineering/...
0
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1answer
570 views

can't make sense of scipy.lognorm [duplicate]

I have been trying to work with random variables in Python and more denerally. My model works with large numbers and lohnormal distributions, but it is very hard to get a clear answer anywhere on the ...
0
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0answers
18 views

Finding p-value and t-value for non-normal distributed datasets (multiple dataframes)

I'm currently working on a project that involves using data from 9 different dataframes. Each dataframe contains 58 rows and 8 columns, and they each contain different data (i.e. Unemployment Rate, ...
0
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0answers
12 views

Check whether two tables come from the same population

I have two data frames and I want to check whether they come from the same population. Essentially, I want to go through the data columns one by one and, depending on column type and how many ...
0
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0answers
99 views

How to compare two classifiers performance using `scipy.stats.ttest_rel`?

I want to compare two classifier performance using T-Test. Using the scipy.stats.ttest_rel: ...
2
votes
1answer
58 views

Mahalanobis distance fixed at root 2

I have this data set of 12 input variables with a size of over 9000. Wanted to find any outliers using mahalanobis distance. As a central point, I decided to take mean and median of all observations, ...
4
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0answers
3k views

Assessing A/B test results using Python

Problem's setting Assume having results of an A/B test. You let you users experience two variants of your website and you counted how many converted: ...
1
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1answer
469 views

ODR residual variance and reduced chi^2 - do the beta uncertainties represent confidence intervals?

I'm looking for the relationship between residual variance of an Orthogonal Distance Regression (ODR) fit (as implemented in scipy.odr) and reduced $\chi^2$. I'm ...
1
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0answers
26 views

How to make chisquare goodness of fit not vulnerable to a single high values?

There is an observation of a process, that I suppose to be a Poisson process. And I'm trying to make a test, to check goodness of fit of my data with Poisson distribution. ...