Causal Impact Analysis in Time Series using R

[@caioferreira4199]

Thank you for sharing such a great content!

[@DaveMH1985]

Thanks a lot for this video. I have no use for it at the moment but I use R for social sciences and it’s always good to know more functions for R for future purposes. You do an excellent job of showing your steps and explain very clearly the results. Subscribed to your channel because of your knowledge on how you utilize R and explanations in other videos that are understandable.

[@AnuragBavaria]

All your videos are quite lucidly explained. Thank you for sharing your knowledge. Looking forward to more videos on time series econometrics.

[@DrewN-xn7kn]

TY so much for this video. Do you have resources for how to choose covariates?

[@mdsajjadhossain3907]

Hi. Thank you for sharing such a informative video. But could not find the codes in the google drive link you shared. Can you please share the codes by creating a folder named "Codes" for this video content?

[@tavaroevanis8744]

What kind of regression does the CausalImpact() function implement?

[@AdilKhan-sh9fv]

What's a good method of choosing covariants?

[@lordamg]

how can you make one with an unweighted average? what is the code for r

[@jingzhao8630]

the original data does not include weekend dates like 29/02/2020 or 01/03/2020. However the "data" does. and the 44 days for the ts start from 27/02 to 10/4 rather than 28/04. Would that be a trouble? Maybe just use: df$date

[@kahuina]

Thank you Justin for this informative video on Causal Impact Analysis. Could also demonstrate how to enter annual time series eg" 2007, 2008, 2009 etc from CVS file.

[@JustinEloriaga]

Just change frequency = 1 in the ts() command

[@adilmasoodkhan4527]

Thank you so much sir keep posting models in R...very interesting. Sir, from where you are

[@iandr4634]

how does the model decide which one is the response variable (in this case : ibcl) ?

[@JustinEloriaga]

The first variable ordered in the cbind()

[@larissabagadion3361]

Hi. This is very helpful. Quick and straight to the point. May I just ask, is there a minimum number of data points required for this analysis both in the pre and post intervention periods? Would this work with a monthly time series with 12 months pre intervention and 3 months post?

[@semmarecipes6647]

Awesome video, explained very well, any idea if this can be done in python?

[@anastasiaachoulias2739]

Hello! Thank you so much for the Video, this helps me very much for my masterthesis :) How will the time.points command for quarterly be? my Dataset starts with 1994 Q1 and ends with 2019 Q4. I have already converted my data from daily/monthly to quarterly data.

[@knowledgeheightsacademy2466]

I keep getting data is not numeric. What could be the problem?

[@JustinEloriaga]

You may have N/As in the data or the date may not be formatted correctly. Kindly check out the lubridate commands.

[@knowledgeheightsacademy2466]

@@JustinEloriaga I have formatted the dates according to your dataset but it's still giving me the same problem

[@patriciaignacio4214]

where's the next session?

[@MrJ17J]

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