---
title: "ngme2 Documentation"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{ngme2 Documentation}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

The full documentation for **ngme2**, including worked examples and rendered
output, is available on the package website:

<https://davidbolin.github.io/ngme2/>

## Getting Started

- [Overview of ngme2](https://davidbolin.github.io/ngme2/articles/ngme2.html):
  Introduction to the package and its main features
- [Installation and configuration (OpenMP)](https://davidbolin.github.io/ngme2/articles/Installation.html):
  How to install ngme2 and enable parallel computation

## Latent Models

- [AR(1) model](https://davidbolin.github.io/ngme2/articles/AR1-model.html):
  Autoregressive order-1 models with non-Gaussian noise
- [Random walk model](https://davidbolin.github.io/ngme2/articles/RW-model.html):
  RW1 and RW2 models
- [Ornstein-Uhlenbeck process](https://davidbolin.github.io/ngme2/articles/ou-process.html):
  Continuous-time OU models
- [SPDE Matérn model](https://davidbolin.github.io/ngme2/articles/SPDE-model.html):
  Spatial models based on the SPDE approach
- [Separable space-time (tensor product) model](https://davidbolin.github.io/ngme2/articles/tensor-product.html):
  Space-time models via tensor products
- [Non-separable space-time model (advection-diffusion)](https://davidbolin.github.io/ngme2/articles/non-separable-model.html):
  Anisotropic and advective space-time models
- [Matérn SPDE model on metric graph](https://davidbolin.github.io/ngme2/articles/matern-on-graph.html):
  Spatial models on networks and metric graphs
- [Bivariate type-G models](https://davidbolin.github.io/ngme2/articles/bivariate.html):
  Joint models for two response variables
- [Using the generic model](https://davidbolin.github.io/ngme2/articles/generic.html):
  How to define custom latent models

## Noise, Estimation, and Prediction

- [Combined Gaussian and NIG noise models](https://davidbolin.github.io/ngme2/articles/normal-nig-noise.html):
  Mixed noise specifications
- [Model estimation and prediction](https://davidbolin.github.io/ngme2/articles/pred-and-est.html):
  How estimation and prediction work in ngme2
- [Models with replicates](https://davidbolin.github.io/ngme2/articles/replicate.html):
  Handling replicated observations
- [Cross-validation](https://davidbolin.github.io/ngme2/articles/cross-validation.html):
  Time series and spatial cross-validation tools
- [Prior templates](https://davidbolin.github.io/ngme2/articles/prior-templates.html):
  Stationary and non-stationary prior specifications
- [SGLD posterior-like sampling](https://davidbolin.github.io/ngme2/articles/sgld-sampling.html):
  Uncertainty quantification via stochastic gradient Langevin dynamics
