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# Giulio Valentino Dalla Riva gvdr

• School of Mathematics and Statistics, University of Canterbury
• Christchurch, New Zealand
Last active Nov 9, 2020
exploring the diagonality score of square matrices
View square_diagonality.jl
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 ### A Pluto.jl notebook ### # v0.12.4 using Markdown using InteractiveUtils # This Pluto notebook uses @bind for interactivity. When running this notebook outside of Pluto, the following 'mock version' of @bind gives bound variables a default value (instead of an error). macro bind(def, element) quote local el = \$(esc(element))
Created Apr 2, 2020
View death_rate_variation.R
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Created Feb 25, 2020
View notations_operators.jl
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 # I'd live to use the usual mathematical notations to do summatories and productories # turns out, in Julia it's pretty easy as long as we keep things simple # as we can just embellish the already defined sum() and prod() function # only tweak is choosing a negative step if we want to sum from i = N to M with N>M # for the summatory: function ∑(f::T;from::Int, to::Int) where T <: Function step_sum = from > to ? 1 : -1 sum(safer(f), range(from, stop = to, step = step_sum)) end
Created Jan 11, 2020
View lottery_ferno.jl
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 using StatsBase, Random, Distributions using Plots # parameters for the simulations blocks = 70000; # Number of ticket blocks tickets = 7000000; # Number of tickets draws = 200; # Number of prizes K = 100000; # Number of lotteries to simulate at each replication R = 100; # Number of replications
Created Apr 12, 2019
View keybase.md

### Keybase proof

I hereby claim:

• I am gvdr on github.
• I am gvdr (https://keybase.io/gvdr) on keybase.
• I have a public key ASBW8zEL_gVtBeSjRwk9_S8_4Xi1x1vlzFwdUc0JDHZDSwo

To claim this, I am signing this object:

Last active Oct 25, 2018
A quick exploratory analysis of the dataset collected by BEtti and Manica (Betti L, Manica A (2018) Human variation in the shape of the birth canal is significant and geographically structured. Proceedings of the Royal Society B 285(1889)
View Birth_Canal_Diversity.md

# Diversity in Birth Canal across the world

A quick exploratory analysis of the dataset collected by BEtti and Manica (Betti L, Manica A (2018) Human variation in the shape of the birth canal is significant and geographically structured. Proceedings of the Royal Society B 285(1889): 20181807.)

We perform classic multidimensional scaling and contrast it with the aggregate means by Region and Population.

Let's load the tidyverse framework to wrangle data and plot it

Created Jul 18, 2018
installation notes for DATA201 and DATA422
View install_notes.txt
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 Data Wrangling Stack -------------------- In this course we will use: - R as default programming language - Tidyverse as the R dialect of choice - The shell commands (bash or zsh), through the terminal
Created Oct 25, 2017
How to group by numeric variables in a dataframe and compute percentiles
View Roberta_Grouping.R
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 # install.packages("tidyverse") # If not yet installed, run this library(tidyverse) # Everything will be don in a tidyverse fashion # This is the kind of dataframe I think Roberta is dealing with. # Vitd is an integer # Age is a numeric # We first need to cut the numeric age into a factor. roberta_df <- tibble( Age = as.integer(runif(100,10,100)), # Age, as an integer Vitd = as.integer(runif(100,80,140)) # Vitd, as an integer
Created Jul 1, 2016
How to handle a matrix in a dataframe. How I do it?
View matrices_dataframe.R
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 #' let's have a matrix n <- 2 m <- 15 my_mat <- matrix(runif(n),m,n) #' let's name those rows, they will be our observations row.names(my_mat) <- letters[1:m]
Created Apr 22, 2015
Compute the ordinary Procrustes sum of squares of two matrices in Julialang. All credits to procOPA {shapes}
View proc_OSS.jl
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 #This is just a quick translation of an ordinary Procrustes sum of squares method, as done in the R function procOPA. #All credits to Dryden, I. L. (2014). shapes package. R Foundation for Statistical Computing, Vienna, Austria. Contributed package. Version 1-1.10. URL http://www.R-project.org #The function are, for now, as they are. I'll be working on them in the future... #Compute a matrix with ones on the main diagonal #and -1/n elsewhere function scaled_ones(n) eye(n) - (1/n) * ones(n,n) end