Articles by Giorgio Garziano

News headlines text analysis

June 14, 2020 | Giorgio Garziano

Are you interested in guest posting? Publish at DataScience+ via your RStudio editor. Category Advanced Modeling Tags Data Management R Programming Text Mining In the present tutorial, I show an introductory text analysis of a ABC-news news headlines dataset. I will have a look to the most common words therein ...
[Read more...]

Earthquake Analysis (4/4): Cluster Analysis

May 18, 2019 | Giorgio Garziano

Are you interested in guest posting? Publish at DataScience+ directly from your editor (i.e., RStudio). Category Basic Statistics Tags Data Visualisation Maps R Programming This is the fourth part of our post series about the exploratory analysis of a publicly available dataset reporting earthquakes and similar events within a ...
[Read more...]

Earthquake Analysis (3/4): Visualizing Data on Maps

May 12, 2019 | Giorgio Garziano

Interested in guest posting? We would love to share your codes and ideas with our community. Categories Basic Statistics Tags Data Visualisation ggplot2 Maps R Programming Tips & Tricks This is the third part of our post series about the exploratory analysis of a publicly available dataset reporting earthquakes and similar ...
[Read more...]

The Mcomp Package

January 2, 2018 | Giorgio Garziano

Makridakis Competitions (also known as the M Competitions or M-Competitions) are a series of competitions organized by teams led by forecasting researcher Spyros Makridakis and intended to evaluate and compare the accuracy of different forecasting methods. So far three competitions have taken place, named as M1 (1982), M2 (1993) and M3 (2000). The ...
[Read more...]

Tennis Grand Slam Tournaments Champions Basic Analysis

December 11, 2017 | Giorgio Garziano

The present tutorial analyses the Tennis Grand Slam tournaments main results from the statistical point of view. Specifically, I try to answer the following questions: – How to fit the distribution of the Grand Slam tournaments number of victories across players? – How to compute the probability of having player’s victories ...
[Read more...]

Outliers Detection and Intervention Analysis

December 4, 2017 | Giorgio Garziano

In my previous tutorial Arima Models and Intervention Analysis we took advantage of the strucchange package to identify and date time series level shifts structural changes. Based on that, we were able to define ARIMA models with improved AIC metrics. Furthermore, the attentive analysis of the ACF/PACF plots highlighted ...
[Read more...]

ARIMA models and Intervention Analysis

October 7, 2017 | Giorgio Garziano

In my previous tutorial Structural Changes in Global Warming I introduced the strucchange package and some basic examples to date structural breaks in time series. In the present tutorial, I am going to show how dating structural changes (if any) and then Intervention Analysis can help in finding better ARIMA ...
[Read more...]

Structural Changes in Global Warming

July 17, 2017 | Giorgio Garziano

In time series analysis, structural changes represent shocks impacting the evolution with time of the data generating process. That is relevant because one of the key assumptions of the Box-Jenkins methodology is that the structure of the data generating process does not change over time. How can structural changes be ...
[Read more...]

Weather forecast with regression models – part 4

June 16, 2017 | Giorgio Garziano

Results so far obtained allow us to predict the RainTomorrow Yes/No variable. In the first part, we highlighted that such factor variable can be put in relationship with the Rainfall quantitative one by: all.equal(weather_data$Rainfall __ 1, weather_data$RainToday == "Yes") As a consequence, we are able so ...
[Read more...]

Weather forecast with regression models – part 2

June 5, 2017 | Giorgio Garziano

In the first part, I introduced the weather dataset and outlining its exploratory analysis. In the second part of our tutorial, we are going to build multiple logistic regression models to predict weather forecast. Specifically, we intend to produce the following forecasts: tomorrow’s weather forecast at 9am of the ... [Read more...]

Weather forecast with regression models – part 1

June 2, 2017 | Giorgio Garziano

In this tutorial we are going to analyse a weather dataset to produce exploratory analysis and forecast reports based on regression models. We are going to take advantage of a public dataset which is part of the exercise datasets of the “Data Mining and Business Analytics with R” book (Wiley) ...
[Read more...]
1 2

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)