Library "MathStatisticsKernelDensityEstimation" (KDE) Method for Kernel Density Estimation kde(observations, kernel, bandwidth, nsteps) Parameters: observations : float array, sample data. kernel : string, the kernel to use, default='gaussian', options='uniform', 'triangle', 'epanechnikov', 'quartic', 'triweight', 'gaussian', 'cosine', 'logistic',...
The following tool smoothes the price data using various methods derived from the Nadaraya-Watson estimator, a simple Kernel regression method. This method makes use of the Gaussian kernel as a weighting function. Users have the option to use a non-repainting as well as a repainting method, see the USAGE section for more information. 🔶 USAGE 🔹 Non...
Returns a moving average allowing the user to control the amount of lag as well as the amplitude of its overshoots thanks to a parametric kernel. The indicator displays alternating extremities and aims to provide potential points where price might reverse. Due to user requests, we added the option to display the moving average as candles instead of a solid...
"In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable." from wikipedia.com KDE function with optional kernel: Uniform Triangle Epanechnikov Quartic Triweight Gaussian Cosinus Republishing due to change of function. deprecated script:
"In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable." from wikipedia.com
Introduction Who doesn't like smooth things? I'd like a smooth market price for christmas! But i can't get it, instead its so noisy...so you apply a filter to smooth it, such filters are called low-pass filters, they smooth and its great but they have lag, so nobody really use them, but they are pretty to look at. Its on a childish note that i will introduce...
This is a moving average with a customizable random kernel. You can shape your kernel by selecting your parameters in the settings window. This is not something that is immediately ready to mess with by just applying it on the chart, it is very useful for people who are researching indicators and developing new tools. To see the shape of your kernel you can plug...
This is a moving average with a customizable gaussian kernel. You can shape your kernel by selecting your parameters in the settings window. This is not something that is immediately ready to mess with by just applying it on the chart, it is very useful for people who are researching indicators and developing new tools. To see the shape of your kernel you can plug...
This is a moving average with a customizable polynomial kernel. You can shape your kernel by selecting your parameters in the settings window. This is not something that is immediately ready to mess with by just applying it on the chart, it is very useful for people who are researching indicators and developing new tools. To see the shape of your kernel you can...