Blog Archives

Spreadsheet Data Manipulation in R

June 15, 2018
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Today I decided to create a new repository on GitHub where I am sharing code to do spreadsheet data manipulation in R.The first version of the repository and R script is available here: SpreadsheetManipulation_inRAs an example I am using a csv fre...

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Data Visualization Website with Shiny

March 25, 2018
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Data Visualization Website with Shiny

My second Shiny app is dedicated to data visualization.Here users can simply upload any csv or txt file and create several plots:Histograms (with option for faceting) Barchart (with error bars, and option for color with dodging and faceting) BoxPlots (with option for faceting) Scatterplots (with options for color, size and faceting) TimeSeries Error bars in barcharts are computed with the mean_se function in ggplot2,...

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Street Crime UK – Shiny App

March 11, 2018
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Street Crime UK – Shiny App

Introduction This is a shiny app to visualize heat maps of Street Crimes across Britain from 2010-12 to 2018-01 and test their spatial pattern. The code for both ui.R and server.R is available from my GitHub at: https://github.com/fveronesi/StreetCrimeUK_Shiny Usage Please be aware that this apps downloads data from my personal Dropbox once it starts and every time the user changes some of the settings....

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Experiment designs for Agriculture

July 25, 2017
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This post is more for personal use than anything else. It is just a collection of code and functions to produce some of the most used experimental designs in agriculture and animal science.  I will not go into details about these designs. If you want to know more about what to use in which situation you can find material at...

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Power analysis and sample size calculation for Agriculture

July 21, 2017
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Power analysis and sample size calculation for Agriculture

Power analysis is extremely important in statistics since it allows us to calculate how many chances we have of obtaining realistic results. Sometimes researchers tend to underestimate this aspect and they are just interested in obtaining significant p-values. The problem with this is that a significance level of 0.05 does not necessarily mean that what you are observing is...

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Generalized Additive Models and Mixed-Effects in Agriculture

July 15, 2017
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Generalized Additive Models and Mixed-Effects in Agriculture

IntroductionIn the previous post I explored the use of linear model in the forms most commonly used in agricultural research.Clearly, when we are talking about linear models we are implicitly assuming that all relations between the dependent variable y and the predictors x are linear. In fact, in a linear model we could specify different shapes for the relation...

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Assessing the Accuracy of our models (R Squared, Adjusted R Squared, RMSE, MAE, AIC)

July 10, 2017
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Assessing the Accuracy of our models (R Squared, Adjusted R Squared, RMSE, MAE, AIC)

Assessing the accuracy of our model There are several ways to check the accuracy of our models, some are printed directly in R within the summary output, others are just as easy to calculate with specific functions. R-Squared This is probably the most commonly used statistics and allows us to understand the percentage of variance in the target variable explained by the...

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Linear Mixed Effects Models in Agriculture

July 10, 2017
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Linear Mixed Effects Models in Agriculture

This post was originally part of my previous post about linear models. However, I later decided to split it into several texts because it was effectively too long and complex to navigate.If you struggle to follow the code in this page please refer to this post (for example for the necessary packages): Linear Models (lm, ANOVA and ANCOVA) in Agriculture Linear...

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Generalized Linear Models and Mixed-Effects in Agriculture

July 10, 2017
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Generalized Linear Models and Mixed-Effects in Agriculture

After publishing my previous post, I realized that it was way too long and so I decided to split it in 2-3 parts. If you think something is missing in the explanation here it may be related to the fact that this was originally part of the previous post (http://r-video-tutorial.blogspot.co.uk/2017/06/linear-models-anova-glms-and-mixed.html), so please look there first (otherwise please post your...

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Linear Models, ANOVA, GLMs and Mixed-Effects models in R

June 28, 2017
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Linear Models, ANOVA, GLMs and Mixed-Effects models in R

As part of my new role as Lecturer in Agri-data analysis at Harper Adams University, I found myself applying a lot of techniques based on linear modelling. Another thing I noticed is that there is a lot of confusion among researchers in regards to what technique should be used in each instance and how to interpret the model. For...

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