R package for testing network dependence
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Updated
Aug 6, 2018 - R
R package for testing network dependence
Case studies for testing the risk of overfitting and the need for variable selection in spatial (-temporal) predictive modelling
Spatial Statistical analyses created using R and RStudio for an "Advanced Statistics for Urban Applications" at Temple University
Time Series Analysis
MATH-342 Time Series course taken at EPFL during Spring 17-18.
Svidzinska, D. (2019). The Application of Directional Univariate Structure Functions Analysis for Studying the Spatial Anisotropy of Environmental Variables. Ekológia (Bratislava), 38(2), 140–153. https://doi.org/10.2478/eko-2019-0011
Time series analysis on NYC births data.
Studies and homework of the Time Series course at FGV EMAp.
Gaussian Process Inference
The influence of time scale on autocorrelation as an early warning indicator of regime shift
This is a final project for a Time Series course. My professor told me I could further work on it.
Corrly For Manufacturing Process
Ordinary least square (OLS) regression analysis carried out in this project. The selected dependent variables are some public health indicators like anxiety, diabetes. We tried to find the independent variables which are responsible for this health hazard.
R codes for Impact of Sampling Rate in Connectivity Analysis (Human Brain Mapping)
Faster, better, smarter ecological niche modeling and species distribution modeling
Current repository depicts R usability for time series modeling. Number of scripts represents preprocessing time series, modeling AR, MA, ARIMA with seasonality, ARCH, GARCH, VAR, VECM including statistical testing process and robust check.
Code computing (Generalized) Kendall's tau and its jackknife variance under serial dependence.
Automatic transcription of piano music in R
Spatial Sampling
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