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Posted on January 29, 2021 at 12:00am 0 Comments 0 Likes
Posted on December 14, 2020 at 5:58am 0 Comments 0 Likes
Bootstrap aggregating (bagging), is a very useful averaging method to improve accuracy and avoids overfitting, in modeling the time series. It also helps stability so that we don’t have to do Box-Cox transformation to the data.
Modeling time series data is difficult because the data are autocorrelated. In this case, moving block bootstrap (MBB) should be preferred because MBB resamples the data inside overlapping blocks to…
ContinuePosted on October 24, 2020 at 11:00pm 0 Comments 0 Likes
In the previous article, we have tried to model the gold price in Turkey per gram. We will continue to do that to find the best fit for our data. When we chose the…
Posted on September 30, 2020 at 10:00am 0 Comments 0 Likes
It is always hard to find a proper model to forecast time series data. One of the reasons is that models that use time-series data often expose to serial correlation. In this article, we will compare k nearest neighbor (KNN) regression which is a supervised machine learning method, with a more classical and stochastic process, autoregressive integrated moving average (ARIMA).
We will use the monthly prices of refined gold futures(XAUTRY) for one gram…
ContinuePosted 12 April 2021
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