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jdify: Retinopathy classification

Thomas Nagler 24 April, 2017

This vignette reproduces the results for the application section of the paper

Nagler, T. (2017). A generic approach to nonparametric function estimation with mixed data. arXiv:1704.07457

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Simulation study for "Asymptotic analysis of the continuous convolution estimator"

Thomas Nagler 15 May, 2017

Required packages:

library(cctools)
library(np)

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Simulation study for kdecopula vignette

Thomas Nagler 15 May, 2017

Required packages:

library("kdecopula")
library("VineCopula")

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title	Appendix to "Generalized Additive Models for Pair-Copula Constructions"
subtitle	Code for the simulation study
author	Thibault Vatter and Thomas Nagler
date	14 August, 2017
output	github_document

Preliminary definitions

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title	Appendix to "Generalized Additive Models for Pair-Copula Constructions"
subtitle	Additional simulations: using BIC for copula family selection
author	Thibault Vatter and Thomas Nagler
date	14 August, 201h7
output	github_document

Preliminary definitions

tnagler

title	Appendix to "Generalized Additive Models for Pair-Copula Constructions"
subtitle	Additional simulations: selecting the GAM structure only for one family
author	Thibault Vatter and Thomas Nagler
date	14 August, 2017
output	pdf_document

Preliminary definitions

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title	Appendix to "Generalized Additive Models for Pair-Copula Constructions"
subtitle	Code for the intraday FX application
author	Thibault Vatter and Thomas Nagler
date	15 August, 2017
output	github_document

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---
title: "RcppThread benchmarks"
output: html_document
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
    collapse = TRUE,
    comment = "#>",
    fig.width = 7,

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Problem statement from Alex Hayes

i have (x, y) pairs generated from two smooth curves, but i don't know which curve each point comes from

is there a way to recover the original curves?https://t.co/h9kL2JEeEV pic.twitter.com/tzy4O1VnrT

— alex hayes (@alexpghayes) June 28, 2022

library(tidyverse)

x <- seq(0, 10, length.out = 100)

unobserved <- tibble(

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# required libraries
library("reticulate")
library("tidyverse")
library("RANN")
library("qrng")
library("readr")
library("ggthemes")


## Python setup -------------------------------------------