# Overview

On this article, I’ll make the local linear trend model to artificial time series data by Stan. Before, I made a local level model on Stan on the article, Local level model to time series data on Stan.
By adding the slope variable to that model, I’ll make the local linear trend model.
I used this book as reference.

# Overview

On this article, I’ll write down the note about the example of tf.variable_scope(), meaning how to arrange the graph for TensorBoard.
The target code is from the article below.
On a tensorboard, without using namespace, the graph information becomes complex. Namespace will solve the problem and makes it easy to debug.

# Overview

On the article below, I switched method on Edward model from variational method to Hamiltonian Monte Carlo.
As an another example, I'll try same thing to the model of the following article.
In a nutshell, I'll make model for an artificial data and get sample by Hamiltonian Monte Carlo.

# Overview

On this article, I tried Hamiltonian Monte Carlo algorithm to the simple data by TensorFlow and Edward.
Edward lets us use variational inference, Gibbs sampling and Monte Carlo method. And by relatively small changes, we can switch the methods. So I'll try simple HML model here.
About Hamiltonian Monte Carlo itself, I'll write another article for it.

# Overview

TensorFlow has the the function of converting Keras model to TensorFlow Estimator. On this article, I checked how to use it.
About the TensorFlow Estimator. Please read the article below and official pages.

Anyway, Keras lets us write neural network model relatively easily. But sometimes we need a model following TensorFlow. On this kind of cases, we write the model by Keras at first and after that can convert it to TnsorFlow's one.

# Overview

On this article, I rewrote the Keras code by tf.keras. From TensorFlow, we can use Keras by tf.keras. But I had never used this. So I checked and it was very simple and easy.

# Overview

On this article, I’ll try golearn package on Golang.
These days, typical environment sets for data science and machine learning are Python, R, R-studio and Jupyter, although it depends on the purposes and phases. When I personally do something, I always use Python and Jupyter. But of course other programming languages have machine learning libraries and those are sometimes used.
Here, I’ll try golearn package, which is the package for machine learning.
This is the official page.
As a first step, through kNN algorithms, I’ll follow the basic step of that.

# Overview

On this article, I'll make the local level model with explanatory variable to time series data on Stan.

Before, I made the simple local level model on Stan. In the practical situation, we frequently need to make model with some explanatory variables. So, I’ll make simple local level model with explanatory variables here.

As a reference, I'm using the following book. This article is dealing with the chapter 5 of the book.

# Overview

Before, I made the simple local level model to time series data. At that article, I just showed the sampled points traced the data. This time, I also do sampling to predict the following points of the data.

Roughly, on the image above, the blue points are data you already have and the red points are the predict target. The purpose of this article is to make model by blue points, data and predict red points, the values of future.

# Overview

On the articles below, I tried local level modeling to time series data on Edward and am still struggling.

#### Time series analysis on TensorFlow and Edward: local level model

Deep learning and Machine learning methods blog

#### Time series analysis on TensorFlow and Edward: local level model:P.S. 1

On the article below, I tried to analyze time series data with local level model. On Stan, I could do it before without problem. But on Edward and TensorFlow, I have been struggling. Deep learning and Machine learning methods blog From the situation above, although it doesn't work well yet, I got some progress.

On this article, I’ll express by Stan what I wanted on Edward. In a nutshell, I’ll write local level model to time series data on Stan.