gongcastro

# Interpretando matrices de correlación en modelos multinivel usando lme4
# Gonzalo García-Castro, gonzalo.garciadecastro@upf.edu

#### cargar paquetes #######################
library(dplyr)     # para manipular variables y usar pipes
library(lme4)      # para ajustar modelos mixtos
library(tibble)    # para pasar nombres de filas como una columna
library(tidyr)     # para pasar de una tabla en formato ancho a una en formato largo
library(janitor)   # para limpiar nombres de variables
library(ggplot2)   # para viualizar datos

gongcastro

#### 2020-07-05_import-multiple ###########################
# Gonzalo García-Castro, gonzalo.garciadecastro@upf.edu
# Center for Brain and Cognition, Universitat Pompeu Fabra
#### set up ###############################################

# load packages
library(dplyr)
library(tidyr)
library(ggplot2)
library(data.table)

gongcastro

#### eyetrackingR with simulated data  ###################
# Gonzalo García-Castro, gonzalo.garciadecastro@upf.edu
# Center for Brain and Cognition, Universitat Pompeu Fabra

#### set up ##############################################

# load packages
library(dplyr)        # for manipulating data
library(tidyr)        # for reshaping dataframes
library(eyetrackingR) # for processing eye-tracking data

gongcastro

library(tidyverse)
library(gganimate)

x <- seq(-4*pi, 4*pi, by = pi/50)
k <- seq(4*pi, -4*pi, by = -pi/50)
y <- t(sapply(x, function(x) sin(x-k)))
d <- as.data.frame(cbind(as.matrix(x), y))
colnames(d) <- c("x", k)
d <- pivot_longer(d, -x, "k", values_to = "y") %>%
  mutate_at(vars(k), as.numeric)

gongcastro

#### mask ----------------------------------------------------------------------

# import packages
library(tidyverse)
library(readxl)
library(stringdist)

#### import data ---------------------------------------------------------------
# you can download the data from https://drive.google.com/file/d/18SeJTiM2-JXR9SOqEg22wdkvNL3OxG3u/view?usp=sharing

gongcastro

#### 2020-10-17-visualising-polynomial-regression -----

#### set up -------------------------------------------

# load packages
library(tidyverse)
library(gganimate)
library(data.table)
library(magick)
library(here)

gongcastro

# extract lexical frequencies from CHILDES

# you may need to install the following packages:
# install.packages(c("dplyr", "stringr", "tidyr", "chidesr"))

get_childes_frequency <- function(
  token, # word(s) form to look up, e.g. c("table", "mesa")
  languages = c("cat", "spa"), # languages in which to look up the word form 
  ... # other arguments (see ?childesr::get_speaker_statistics)
){

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# animate the Beta distribution

# parameter vectors
x = collect(0.01:0.01:0.99); # sampling space
α = collect(0.1:0.1:10);
β = collect(0.1:0.1:10);
# only β=5 is used, but I don't want to mess up the code

# extract probability densities for all combinations of parameters
y = zeros(length(x), length(α), length(β)); # pre-alocate

gongcastro

# get audio duration

# set up ----
library(audio)
library(purrr)
library(dplyr)
library(tidyr)
library(ggplot2)
library(PraatR)
library(stringr)

gongcastro

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