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Now showing items 1-5 of 5
Conditional Clustering Method on KNN for Big Data
(2024)
This thesis endeavors to address the challenges faced by k-nearest neighbor (KNN) classifiers when handling big data, particularly concerning large storage requirements and extended training times. The proposed solution ...
(1.9MB)
PAL versus SMC: Two Approaches in Compartmental Modeling
(2024)
Partially Observed Markov Process (POMP) models have been extensively employed in epidemiological modeling over the past several decades to understand disease patterns and inform policy-making. Although the observation ...
(1.3MB)
Model Based Inference of Stochastic Volatility via Iterated Filtering
(2024)
The Heston stochastic volatility model is one of the most widely studied stochastic volatility models, in which the variance follows a Cox–Ingersoll–Ross process. Estimating this model under the physical measure is ...
(5.1MB)
Large N, Small T, Multiple P: A Causal Matrix Completion Method for CRM Panel Data
(2024)
The prototypical customer relationship management (CRM) panel structure is composed of many customers (large N), with short histories (small T), and multiple outcome metrics (multiple P). Our paper aims to tackle the ...
(3.2MB)
Kernel Dimension Reduction with Missing Data
(2024)
Kernel dimension reduction (KDR), a form of sufficient dimension reduction (SDR), is a framework for identifying potentially nonlinear multivariate relation- ships between high-dimensional predictors X and outcomes Y , ...
(714.9KB)