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Adam Check
Добавлен 16 ноя 2017
Time Series Forecasting Example in RStudio
Demonstrates the forecasting process with a business example - the monthly dollar value of retail sales in the US from 1992-2017. See links below for CSV file and textbook.
Link to CSV file: adamjcheck.com/real_sales_per_day.csv
Link to Hyndman and Athanasopoulos: otexts.org/fpp2/
Link to CSV file: adamjcheck.com/real_sales_per_day.csv
Link to Hyndman and Athanasopoulos: otexts.org/fpp2/
Просмотров: 144 556
dang one more year in your forecast and you could've tried to predict for covid xd, thanks for the video im also working with retail sales but think that no model can be really good imo
Thanks, Adam! This was really helpful!
the best, most comprehensive video i have seen so far!!
thank youu sooooo much it"s saving my masters😭🙇♀
Can't get to the CSV file. Have another?
Links to CVS do not work. Why don't you remove the link? Is the data not available?
Hi Is there any chance you can check my assignment in Forecasting in Business and Economics on time Series and analysis. Just corrections and see if it nets the objectives of the report. Thanks
One of the best videos.i like the real data and the different steps of submodes and their improvement. Excellent work!
You are awesome!
Thank you very much, this is the most helpful video I have ever seen💕💕
thank you so much, you saved my life
this saved me, thanks
Absolutely wonderful video. Thanks a million
This is such an excellent walk-thru explained very well. Thanks so much for this work!
Very helpful. Thank you!
Very useful video. You are so clear and coherent in presenting it. Thanks friend.
sad. after 4 years only one upload! this is the best Arima + forecast I have ever seen...
I have a peculiar data set with hourly averages in the month, different from your data in which there is only one value per month (monthly). So, in my case, how would I turn it into a time series??
very explicit, you absolute justice to time series explanation
someone can send the csv file ? his url doesnt work for me...
fantastic job!
Really nice and helpful... Thanks!
now i am in a good mood
You should consider putting a course together, you by far have the best communication on RUclips topped off with astounding knowledge on statistics and code.
Great stuff. What if I have to forecast many time serieses ? Is there a way to automate their forecast en masse?
Beyond the obvious knowledge of both R and statistics, you hold outstanding communication skills. Great job!
Awesome example and explanation! Thanks from 2022 ;-)
Amazing, in just 30 minutes you covered the topic and code so well. Thanks a lot!
What about LSTM methods or neural methods?
Amazing content, thank you! The only thing I am confused about is the argumet D in the auto.arima() model! so if I make D = 1 this means i am removing seasonality so should I make D = 0 to include seasonality in?
d = 1 removes the trend
This is an outstanding video. I'm new to R and forecasting - and you got me up and running in 37 minutes and 52 seconds! I really appreciate your clear explanations of the various options; I'm excited to check out fpp3, and confident that because of your excellent instruction I'll be able to move forward with forecasting software costs for my workplace. Many thanks!
Amazing Tutorial!!!
Great stuff and clean coding 👌
Thank you good sir
Oziiiiii naber
Really well explained thank you very much, this was my first project/tutorial in R and R studio. Unlike your data mine has a big spike, it is near the beginning of the 2.5 year dataset (by month). Should I remove it, find a way to normalise it or maybe delete the month in question and allow the tool to fill that month with a "normal amount" some how? Any comment welcome :-)
Hi Tom, unfortunately there is no one-size-fits-all solution to this problem. There are a few approaches you could take. One is to replace the extreme value with another large value (with the same sign), but that is more in-line with the historical patterns of the data (e.g., replace the spike with +/- 4*sd(Y), or the 1st or 99th percentile of the data). Another approach is to include a dummy variable. The Arima and auto.arima functions allow you to include a dummy through the xreg option. Another approach is to consider an alternate model of the variance of the model (e.g., student t errors instead of normal errors, a GARCH model for the variance, or an SV model for the variance, etc.). Depending on the exact nature of your spike (e.g., it only lasts one period, it lasts several periods, it is a large positive followed by a large negative, there are occasional spikes that occur at irregular intervals, etc.) these different options will work more or less well. I considered some of these options in more detail in this chapter I wrote for a forecasting class I was teaching after the pandemic. See: adamjcheck.com/Chapter_10_Outliers.pdf
@@adamcheck9108 Thanks for coming back and your link, I'll take a read.
Thanks a lot! I had a task to detect an outlier in forecasting analysis in R but literally had no prior experience in R! You just saved me. This tutorial is so beginner-friendly and easy to take notes! Can't thank you enough
Thanks, this was really helpful.
The link to the data is not working?
It works for me, but you may need to change your browser's security settings to allow file downloads over an insecure connection (in firefox it gives me a wanring, but lets me download it).
@@adamcheck9108 , I right clicked and did a safe as and it worked.
Hi, I have a question to ask. In your adjusted data, whether things like CPI or number of days in each month have to be done manually, e.g. search google and type in each cell? Is there a way to do it faster? I would love to hear from you guys, thanks a lot. <3
I believe there is a built-in monthdays() function that will give the days in each month. So if you have monthly data, you can do something like Y/monthdays(Y) to get the daily average in each month.
Great help, Thanks a million.
Hello, Thanks so much for sharing this great piece. Please, how can you forecast by months?
Larger font on screen, please?
Hi Adam! very helpful video. But I have a question. When using the "diff" function, it gave an error.The error was " Error in `-.default`(r, tsLag(r, -lag)) : non-numeric argument to binary operator". Can you help me please to solve this issue. It is emergency
This is a very helpful video. Thank you! I do have a question. How do you suggest I address negative prediction intervals? I am forecasting sales and I can't imagine having negative sales in a given period.
This is just amazing! A lot simpler than I imagined... Thank you for doing this
The data download isn't available now.
just saved my university project. thank you guru
you really really really helped me today thank god i found this video today
24:21
Please make more videos!!!!