Exploratory data analysis with noisy measurements

Geographical Analysis of COVID-19 Epidemiology in Iran with Exploratory Spatial Data Analysis Approach (ESDA)

Background and Aim: The use of geophysical analysis of the epidemiology to identify geographical factors affecting the prevalence of the disease can be effective on community health policies to control the prevalence of the virus. Therefore, the present study is a geographical analysis of the COVID-19 epidemiology in Iran. Therefore, the purpose of this study is the geographical analysis of co...

Protein Conformational Flexibility Analysis with Noisy Data

Protein conformational changes play a critical role in biological functions such as ligand-protein and protein-protein interactions. Due to the noise in structural data, determining salient conformational changes reliably and efficiently is a challenging problem. This paper presents an efficient algorithm for analyzing protein conformational changes, when the data is noisy. It applies a statist...

Exploratory Data Analysis with Bivariate Dependence Functions

Dependence functions are used to construct joint distributions with fixed marginals. They can shed light on relationships among associated random variables. Many dependence functions have been proposed and standardized. However, there has not been an attempt to understand why certain dependence functions are used and what makes certain dependence functions better than others in solving practica...

Exploratory Data Analysis with Interactive Evolution

We illustrate with two simple examples how Interactive Evolutionary Computation (IEC) can be applied to Exploratory Data Analysis (EDA). IEC is particularly valuable in an EDA context because the objective function is by definition either unknown a priori or difficult to formalize. The first example involves what is probably the simplest possible transformation of data: linear projections. Whil...

Exploratory data analysis