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
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
title | subtitle | author | date | output |
---|---|---|---|---|
Appendix to "Generalized Additive Models for Pair-Copula Constructions" |
Code for the intraday FX application |
Thibault Vatter and Thomas Nagler |
15 August, 2017 |
github_document |
--- | |
title: "RcppThread benchmarks" | |
output: html_document | |
--- | |
```{r setup, include = FALSE} | |
knitr::opts_chunk$set( | |
collapse = TRUE, | |
comment = "#>", | |
fig.width = 7, |
i have (x, y) pairs generated from two smooth curves, but i don't know which curve each point comes from
— alex hayes (@alexpghayes) June 28, 2022
is there a way to recover the original curves?https://t.co/h9kL2JEeEV pic.twitter.com/tzy4O1VnrT
library(tidyverse)
x <- seq(0, 10, length.out = 100)
unobserved <- tibble(
# required libraries | |
library("reticulate") | |
library("tidyverse") | |
library("RANN") | |
library("qrng") | |
library("readr") | |
library("ggthemes") | |
## Python setup ------------------------------------------- |