stochastic | common stochastic processes with native JavaScript | Functional Programming library

 by   NathanEpstein JavaScript Version: 0.0.14 License: No License

kandi X-RAY | stochastic Summary

kandi X-RAY | stochastic Summary

stochastic is a JavaScript library typically used in Programming Style, Functional Programming applications. stochastic has no bugs, it has no vulnerabilities and it has low support. You can install using 'npm i stochastic' or download it from GitHub, npm.

Simulation of common stochastic processes with native JavaScript
Support
    Quality
      Security
        License
          Reuse

            kandi-support Support

              stochastic has a low active ecosystem.
              It has 227 star(s) with 17 fork(s). There are 11 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 0 open issues and 1 have been closed. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of stochastic is 0.0.14

            kandi-Quality Quality

              stochastic has 0 bugs and 0 code smells.

            kandi-Security Security

              stochastic has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              stochastic code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              stochastic does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              stochastic releases are not available. You will need to build from source code and install.
              Deployable package is available in npm.
              Installation instructions, examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed stochastic and discovered the below as its top functions. This is intended to give you an instant insight into stochastic implemented functionality, and help decide if they suit your requirements.
            • Double - Law Distance
            Get all kandi verified functions for this library.

            stochastic Key Features

            No Key Features are available at this moment for stochastic.

            stochastic Examples and Code Snippets

            DOSNES,How to use?
            JavaScriptdot img1Lines of Code : 20dot img1no licencesLicense : No License
            copy iconCopy
            % Generate data and its similarity matrix
            X = randn(1000,10);
            D = pdist2(X,X,'squaredeuclidean');
            P = exp(-D);
            
            % Normalize the similarity matrix to be doubly stochastic by Sinkhorn-Knopp method
            for i = 1:100
                P = bsxfun(@rdivide,P,sum(P,1));
                  
            copy iconCopy
            @ARTICLE{9127137,
            
              author={A. {Kuzdeuov} and D. {Baimukashev} and A. {Karabay} and B. {Ibragimov} and A. {Mirzakhmetov} and M. {Nurpeiissov} and M. {Lewis} and H. {Atakan Varol}},
              journal={IEEE Journal of Biomedical and Health Informatics}, 
              ti  
            Noisy linear cosine decay .
            pythondot img3Lines of Code : 92dot img3License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def noisy_linear_cosine_decay(learning_rate,
                                          global_step,
                                          decay_steps,
                                          initial_variance=1.0,
                                          variance_decay=0.55,
                              
            Creates a Zero bias for a given strategy .
            pythondot img4Lines of Code : 87dot img4License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def _zero_debias(strategy, unbiased_var, value, decay):
              """Compute the delta required for a debiased Variable.
            
              All exponential moving averages initialized with Tensors are initialized to 0,
              and therefore are biased to 0. Variables initialized   
            Linear cosine decay .
            pythondot img5Lines of Code : 82dot img5License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def linear_cosine_decay(learning_rate,
                                    global_step,
                                    decay_steps,
                                    num_periods=0.5,
                                    alpha=0.0,
                                    beta=0.001,
                                    n  
            CM_Stochastic Highlight Bars by Chris Moody?? Alerts
            JavaScriptdot img6Lines of Code : 83dot img6License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            //@version=3
            study("Stoch HL", overlay=true)
            
            //Created by ChrisMoody on October 23, 2014 by user request - belgusinc
            //Changes Barcolor when Stochastic is Overbought Oversold.
            
            //Necessary for Highlight Bars
            //Only Necessary if you want y
            Generate a Dataframe that follow a mathematical function for each column / row
            JavaScriptdot img7Lines of Code : 25dot img7License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            import pandas as pd
            import numpy as np
            from math import exp, sqrt
            
            def monte_carlo_df(nrows,
                               ncols,
                               col_1_val,
                               r=0.03,
                               q=0.5,
                               sigma=0.002,
                 
            Best iterative way to calculate the fundamental matrix of an absorbing Markov Chain?
            JavaScriptdot img8Lines of Code : 38dot img8License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            import networkx as nx
            import numpy as np
            import scipy.sparse as sp
            import scipy.sparse.linalg as spla
            
            def example(n):
                """Generate a very simple transition matrix from a directed graph
                """
                g = nx.DiGraph()
                for i in xrange(n

            Community Discussions

            QUESTION

            How to add new columns to pandas data frame using .loc
            Asked 2022-Feb-28 at 21:40

            I am calculating very simple daily stock calculations in data frame ( for e.g. SMA, VWAP, RSI etc). After I upgraded to anaconda 3.0, my code stopped working and gives followed error. I don't have much experience in coding and need some help.

            KeyError: "Passing list-likes to .loc or [] with any missing labels is no longer supported. The following labels were missing: Index(['RSI', 'ZONE'], dtype='object'). See https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike"

            Followed is the code.

            ...

            ANSWER

            Answered 2022-Feb-28 at 21:40

            A few lines need to be tweaked

            1. Instead of

            Source https://stackoverflow.com/questions/71300628

            QUESTION

            is it efficient to define random number generator inside function integrator?
            Asked 2022-Feb-22 at 10:14

            Consider an Euler integrator that solves a stochastic differential equation:

            ...

            ANSWER

            Answered 2022-Feb-22 at 10:14

            Seeding a PRNG if often costly and should usually only be done once during the whole program run so, no, this is not efficient.

            I suggest that you break the creation of the PRNG out into a separate function that has a static PRNG (only initialized once).

            Source https://stackoverflow.com/questions/71218664

            QUESTION

            Expectation Maximization using a Poisson likelihood function
            Asked 2022-Feb-11 at 15:57

            I am trying to apply the expectation-maximization algorithm to estimate missing count data but all the packages in R, such as missMethods, assume a multivariate Gaussian distribution. How would I apply the expectation-maximization algorithm to estimate missing count data assuming a Poisson distribution?

            Say we have data that look like this:

            ...

            ANSWER

            Answered 2022-Feb-11 at 15:57

            QUESTION

            how to apply a function on several simulated graphs in R
            Asked 2022-Feb-04 at 09:40

            I need a vector (or list) of several results of a function on several simulated graphs (eg assortativity). This is to emulate a Monte Carlo procedure, to perform a segregation analysis with stochastic block models instead of Erdos-Renyi models. This allows to differentiate the probability of links between two types of actors due to the design of the data collection, with a method similar to conditional uniform graphs. I have tried unsuccessfully with the following loop:

            ...

            ANSWER

            Answered 2022-Feb-04 at 09:40

            I think replicate is the thing you may need

            Source https://stackoverflow.com/questions/70979920

            QUESTION

            Encountering a TypeError: can't multiply sequence by non-int of type 'float' when creating an SGD algorithm
            Asked 2022-Jan-27 at 08:04
            # We first define the observations as a list and then also as a table for the experienced worker's performance.
            
            Observation1 = [2.0, 6.0, 2.0]
            Observation2 = [1.0, 5.0, 7.0]
            Observation3 = [5.0, 2.0, 1.0]
            Observation4 = [2.0, 3.0, 8.0]
            Observation5 = [4.0, 4.0, 0.0]
            ObservationTable = [
                                Observation1,
                                Observation2,
                                Observation3,
                                Observation4,
                                Observation5
                                ]
            
            # Then we define our learning rate, number of observations, and the epoch counters we will be utilizing (10, 100, and 1000).
            
            LearningRate = 0.01
            ObservationCounter = 5
            EpochVersion1 = 10
            EpochVersion2 = 100
            EpochVersion3 = 1000
            
            # Thus, we are now ready to define the Stochastic Gradient Descent Algorithm:
            
            def StochasticGradientDescent(EpochCounter):
                Theta0 = 10.0
                Theta1 = 0.0
                Theta2 = -1.0
            
                while (EpochCounter != 0):
            
                    ObservationCounter = 5
            
                    while (ObservationCounter >= 0):
            
                        Theta0_Old = float(Theta0)
                        Theta1_Old = float(Theta1)
                        Theta2_Old = float(Theta2)
            
                        n = 5 - ObservationCounter
                        x = ObservationTable [n]
                        x0 = float(x[0])
                        x1 = float(x[1])
                        x2 = float(x[2])
            
                        Theta0_New = Theta0_Old - LearningRate*[(Theta0_Old+Theta1_Old*float(x0)+Theta2_Old*float(x1))-float(x2)]
                        Theta1_New = Theta1_Old - LearningRate*[(Theta0_Old+Theta1_Old*float(x0)+Theta2_Old*float(x1))-float(x2)]*float(x0)
                        Theta2_New = Theta2_Old - LearningRate*[(Theta0_Old+Theta1_Old*float(x0)+Theta2_Old*float(x1))-float(x2)]*float(x1)
            
                        print(Theta0_New, Theta1_New, Theta2_New)
                        ObservationCounter -= 1
            
                    else:
                        EpochCounter -= 1
                        if (EpochCounter == 0):
                           print(Theta0_New, Theta1_New, Theta2_New)
            
            
            StochasticGradientDescent(int(EpochVersion1))
            
            
            ...

            ANSWER

            Answered 2022-Jan-27 at 08:04

            I do not know very much about stochastic gradient descent but there are two improvements that I spot in your code.

            Firstly, the error is caused because you try to multiply a float with a list and add that to a float. This is fixed by using round brackets instead of square:

            Source https://stackoverflow.com/questions/70874703

            QUESTION

            How can use multiple indicators() in version5
            Asked 2022-Jan-25 at 14:46

            I'm trying to use custom Stochastic and RSI in version5 but it only allows me to use 1 indicator in the script.

            I've tried using study but that doesn't work.

            How can I fix this?

            I've tried removing version version5 and using only study but that breaks the RSI code.

            PS - not a programmer. Know very little about coding, trying to learn though!

            ...

            ANSWER

            Answered 2022-Jan-25 at 13:23

            You can only have 1 indicator() or study() tag in a script.
            You have to merge the code of both, like this for example:

            Source https://stackoverflow.com/questions/70849218

            QUESTION

            Cannot print bibliography despite changing backend to biber, print bibliography says empty bibliography
            Asked 2022-Jan-12 at 15:03

            Hi I have tried a lot of things and gone through several questions posted earlier but I can't seem to get my bibliography to print. I get the following errors:

            1. Empty Bibliography (when I write \printbibliography)
            2. Undefined Control Sequence (when I overwrite file contents for reference.bib in my main.tex)

            Things I have tried:

            1. Changing the backend to biber and biblatex both. None worked.
            2. Adding overwrite file contents and reinputting the bib file content in main.tex and then cite them one by one using \citep{}
            3. Changing styles

            I have posted all of my code here (main.tex) in case there are some other code lines that might be messing with the use package of bibliography.

            ...

            ANSWER

            Answered 2022-Jan-12 at 15:03

            Several problems:

            • \citep is a natbib macro. If you want to use it in biblatex, you must use the natbib option when you load biblatex.

            • you shouldn't load package more then once. You MUSTN'T load them more than once with different options. An error message will explicitly tell you about the option clash for the geometry package

            • the syntax \begin{filecontents*}[overwrite]{\references.bib} is wrong, references.bib should just be the filename, not a (non-existent) macro

            • the note field in the wikipedia entry caused come probelems, so I moved it to another field.

            Source https://stackoverflow.com/questions/70683370

            QUESTION

            Translating Stata commands into R (Stochastic Frontier Analysis)
            Asked 2022-Jan-10 at 03:09

            I have very little familiarity with Stata, and I am working on interpreting the code below (which concerns stochastic frontier analysis) in order to translate into R:

            ...

            ANSWER

            Answered 2022-Jan-10 at 03:08

            u_e is just the name supplied for a new variable. What's important is that it contains estimates of minus the natural log of the technical efficiency via E(u|e)

            Hence exp(-u_e) is just the estimated technical efficiency.

            See https://www.stata.com/manuals/rfrontierpostestimation.pdf

            Source https://stackoverflow.com/questions/70647300

            QUESTION

            Combining NULL and numeric value in Shiny
            Asked 2022-Jan-07 at 23:49

            I would like to replicate the following R code in Shiny

            ...

            ANSWER

            Answered 2022-Jan-07 at 23:49

            numericInput default to NA when it's empty. Maybe a workaround can be:

            Source https://stackoverflow.com/questions/70627604

            QUESTION

            PyTorch training loop within a sklearn pipeline
            Asked 2021-Dec-29 at 18:42

            What I am playing around with right now is to work with PyTorch within a pipeline, where all of the preprocessing will be handled.

            I am able to make it work. However, the results I am getting are a bit off. The loss function seems to be not decreasing and gets stuck (presumably in local optima?) as the training loop progresses.

            I follow the standard PyTorch training loop and wrap it inside the fit method as this is what sklearn wants:

            ...

            ANSWER

            Answered 2021-Dec-29 at 14:32

            The problem in this implementation is in the fit method.

            We are comparing prediction and design matrix

            Source https://stackoverflow.com/questions/70518288

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install stochastic

            You can install using 'npm i stochastic' or download it from GitHub, npm.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
            Find more information at:

            Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items

            Find more libraries
            Install
          • npm

            npm i stochastic

          • CLONE
          • HTTPS

            https://github.com/NathanEpstein/stochastic.git

          • CLI

            gh repo clone NathanEpstein/stochastic

          • sshUrl

            git@github.com:NathanEpstein/stochastic.git

          • Stay Updated

            Subscribe to our newsletter for trending solutions and developer bootcamps

            Agree to Sign up and Terms & Conditions

            Share this Page

            share link

            Consider Popular Functional Programming Libraries

            ramda

            by ramda

            mostly-adequate-guide

            by MostlyAdequate

            scala

            by scala

            guides

            by thoughtbot

            fantasy-land

            by fantasyland

            Try Top Libraries by NathanEpstein

            Dora

            by NathanEpsteinPython

            Pavlov.js

            by NathanEpsteinC++

            D3xter

            by NathanEpsteinJavaScript

            datakit

            by NathanEpsteinJavaScript

            reinforce

            by NathanEpsteinPython