stochastic | common stochastic processes with native JavaScript | Functional Programming library
kandi X-RAY | stochastic Summary
kandi X-RAY | stochastic Summary
Simulation of common stochastic processes with native JavaScript
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- Double - Law Distance
stochastic Key Features
stochastic Examples and Code Snippets
% 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));
@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
def noisy_linear_cosine_decay(learning_rate,
global_step,
decay_steps,
initial_variance=1.0,
variance_decay=0.55,
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
def linear_cosine_decay(learning_rate,
global_step,
decay_steps,
num_periods=0.5,
alpha=0.0,
beta=0.001,
n
//@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
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,
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
Trending Discussions on stochastic
QUESTION
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 21:40A few lines need to be tweaked
- Instead of
QUESTION
Consider an Euler integrator that solves a stochastic differential equation:
...ANSWER
Answered 2022-Feb-22 at 10:14Seeding 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).
QUESTION
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 15:57Defining x0
:
QUESTION
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 09:40I think replicate
is the thing you may need
QUESTION
# 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 08:04I 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:
QUESTION
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 13:23You can only have 1 indicator()
or study()
tag in a script.
You have to merge the code of both, like this for example:
QUESTION
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:
- Empty Bibliography (when I write \printbibliography)
- Undefined Control Sequence (when I overwrite file contents for reference.bib in my main.tex)
Things I have tried:
- Changing the backend to biber and biblatex both. None worked.
- Adding overwrite file contents and reinputting the bib file content in main.tex and then cite them one by one using \citep{}
- 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 15:03Several problems:
\citep
is a natbib macro. If you want to use it in biblatex, you must use thenatbib
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) macrothe
note
field in the wikipedia entry caused come probelems, so I moved it to another field.
QUESTION
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 03:08u_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
QUESTION
I would like to replicate the following R code in Shiny
...ANSWER
Answered 2022-Jan-07 at 23:49numericInput
default to NA
when it's empty. Maybe a workaround can be:
QUESTION
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 14:32The problem in this implementation is in the fit
method.
We are comparing prediction and design matrix
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