New Series of Time Series: Part 3 (Holt’s Exponential Smoothing)

In the last posts, I have explained the main concepts behind the Timeseries (Post 1) and  in the second one a simple forecasting approach name as “Exponential Smoothing” has been proposed Post 2. In this post I am going to show how to do see the error of forecasting and also how to forecast when ...

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New Series of Time Series: Part 2 (Exponential Smoothing)

In the last post , I have explained the main concepts behind the timeseries. In this post, I am going to show how we can forecast for some periods. In the last post, I have mentioned that there is a possibility to have “seasonality” “Trend” and  errors (residual) in one dataset: Seasonality+Trend+Residual we call it as ...

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Optimization Problem in Power BI using R scripts: Part 3

As I have discussed before, R is not only for doing Machine Learning (despite it is a really good tools for it), it also can be used for helping managers to so decision support. In the last two posts (Post 1 and 2), I have explained the main concepts behind the optimization problems. Also, how ...

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Optimization Problem in Power BI using R scripts: Part2

In the last post, I have explained the main concepts and usage of “Optimization” problems and “Linear Programming”. In this post, I am going to explain a simple example of solving an optimization problems from [1]. Imagin, we have a company that produce Product 1 and Product 2,  we want to maximize the profit of ...

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Optimization Problem in Power BI using R scripts: Part1

There are some traditional problems in most of industries like how we can reach maximum profit, sales, production or how we can minimize our cost and loos. These types of problems can be seen in different areas such as microeconomic and company management, such as planning, production, transportation, technology . Although the modern management issues ...

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