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mcmc_regression

https://events.mpifr-bonn.mpg.de/indico/event/30/material/slides/12.pdf

mean_in_gap

Mean of data after certain gap, example 1,5,9,...so on.

milstein_method

Milstein method is a technique for the approximate numerical solution of a stochastic differential equation

minimum_norm_geo

Geometric way to calculate min norm

min_norm_solution

Consider a linear system of equations Ax=b. If the system is overdetermined, the least squares (approximate) solution minimizes ||b−Ax||2. Some source sources also mention ||b−Ax||. If the system is underdetermined one can calculate the minimum norm solution. But it does also minimize ||b−Ax||

mle_with_missingdata

ml_dili_prediction

Drug induced liver injury prediction by ML Algorithms, feature selection and ROC analysis

modified_newtons

Modified form of newtons method. It is faster and gives good convergence when we want to minimize a function in multidimension.

monte_carlo_simulation

multinomial_logistic_regression-

multinomial logistic regression is a classification method that generalizes logistic regression to multiclass problems, i.e. with more than two possible discrete outcomes.

multiple_linear_regression

Multiple Linear Regression, its Statistical Analysis, and Application in Energy Efficiency. Exploratory analysis; model selection; MLR; K fold cross-validation

multivariate_newton

faster multivariate newton method

multivariate_newton_raphson

nelder-mead-method

The Nelder Mead algorithm is developed using a simplex, which is a generalized triangle in N dimensions, and it follows an efective and computationally compact scheme.

non-negative_matrix_factorization

NMF in Matlab on Heart failure data sets

openintro

Data sets (and perhaps other utilities) to accompany Open Intro Stats with Randomization and Simulation

parameter_estimation_coupled_ode

pca_for_ordinal_data

Principal Component Analysis (PCA) needs Polychoric correlation is suitable for ordinal variables with more than two categories, while polyserial correlation is appropriate when one of the variables is continuous. These correlations estimate the underlying latent (unobserved) continuous variables that give rise to the observed ordinal categories.

polynomial-curve-fitting

Polynomial curve fitting/ polyfit for covid-19 data set

power-iteration

Proximal gradient methods are a generalized form of projection used to solve non-differentiable convex optimization problems.

proximal-gradient-descent

https://www.stat.cmu.edu/~ryantibs/convexopt/lectures/prox-grad.pdf

proximal_gradient_for_lasso

proximal_gradient_for_ridge_regression

qr_factorization

Simple and fast way

regression_tree

richardson_extrapolation

runge_kutta_order-4

save_mat_file

Convert python data to matlab MAT files

simpson_rule

Simpson's rule uses a quadratic polynomial on each subinterval of a partition to approximate the function f(x) and to compute the definite integral

spectral-clustering