R News from another blog for R community
In : import statsmodels.datasets as datasets In : import sklearn.metrics as metrics In : from numpy import log In : from pyearth import Earth as earth In : boston =...continue reading.
In the operational loss calculation, it is important to use CPI (Consumer Price Index) adjusting historical losses. Below is an example showing how to download CPI data online directly from...continue reading.
When conducting Cohort Analysis, one of the most important measures is Customer Retention Rate. I will share a few ideas for visualizing this parameter When conducting Cohort Analysis, one of...continue reading.
In : # LOAD PACKAGES In : import pandas as pd In : import numpy as np In : from sklearn import preprocessing as pp In : from sklearn import...continue reading.
A new package has hit the CRAN shelves this week. While knitr is one of the most useful R packages in existence, ezknitr is a simple extension to it that...continue reading.
Poisson and Negative Binomial regressions are two popular approaches to model frequency measures in the operational loss and can be implemented in Python with the statsmodels package as below: Although...continue reading.
When modeling severity measurements in the operational loss with Generalized Linear Models, we might have a couple choices based on different distributional assumptions, including Gamma, Inverse Gaussian, and Lognormal. However,...continue reading.
I spent much of the last two months reading Lehmann & Romano “Testing Statistical Hypotheses” (3rd ed.) and Lehmann & Casella “Theory of Point Estimation” (2nd ed.), abbr. TSH and...continue reading.
I’m currently working on a paper (with my colleague Vincent Vergnat who is also a Phd candidate at BETA) where I want to estimate the causal impact of the birth...continue reading.