Examples of Exponential distribution
The exponential distribution is commonly used to model the time between events in a Poisson process. It is defined by a single parameter, , which is the rate parameter. The probability density function (PDF) of… Examples of Exponential distribution
Finding the derivative of a composite function with chain rule
The chain rule is a fundamental technique in calculus for finding the derivative of a composite function. Here are some examples that illustrate its use: Example 1: Simple Composite Function Let’s find the derivative of… Finding the derivative of a composite function with chain rule
examples of limit computations
Here are a few more examples of limit computations involving various techniques: Example 1: Basic Limit Find the limit: Solution: This is a basic limit where we can directly substitute : Example 2: Limit Involving… examples of limit computations
Mathematical functions
A function in mathematics and computer science is a relation between a set of inputs and a set of permissible outputs. It assigns each input exactly one output. Functions can be simple or complex, depending… Mathematical functions
denoising via dimension reduction in python
Dimension reduction methods like Principal Component Analysis (PCA) or Singular Value Decomposition (SVD) can be used for denoising data because they work by retaining the most important features (or dimensions) that capture the majority of… denoising via dimension reduction in python
why we can & probably should use missing at random imputation methods for data that’s not missing at random?
Missing At Random (MAR) imputation methods are based on the assumption that the chance of missing data is not related to the missing data itself, but might be related to some of the observed data.… why we can & probably should use missing at random imputation methods for data that’s not missing at random?
Missing data analysis: where’s your missing piece?
Why missing data occurs can be attributed to various reasons, including human error, malfunctioning equipment, or even intentional omission. It is important to handle missing data because it can significantly impact the reliability and accuracy… Missing data analysis: where’s your missing piece?
Imputation using SoftImpute in python
SoftImpute is a matrix completion algorithm in Python that allows you to fill in missing data in your dataset. This method is based on Singular Value Decomposition (SVD) and Iterative Soft Thresholding. Here’s a basic… Imputation using SoftImpute in python
Multiple Imputation with Chained Equations method & Python codes
MICE (Multiple Imputation by Chained Equations) is a statistical method used for handling missing data by creating multiple imputations or “guesses” for the missing values. It works by using a set of regression models to… Multiple Imputation with Chained Equations method & Python codes