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This question is similar to yours (they had 90 days ...you have 30 days ) Robust time-series regression for outlier detection . The whole idea is to build a model for the daily totals and then use daily total as a predictor variable for each of the 24 hourly models.

edit after a (visual) review of your data ..it is clear that have fixed daily effects and fixed hourly effects and outliers and a level shift (down) ... that having been said there may also be some arima structure ..

Only your data knows what else is needed .

This question is similar to yours (they had 90 days ...you have 30 days ) Robust time-series regression for outlier detection . The whole idea is to build a model for the daily totals and then use daily total as a predictor variable for each of the 24 hourly models.

edit after a (visual) review of your data ..it is clear that have fixed daily effects and fixed hourly effects and outliers and a level shift (down) ... that having been said there may also be some arima structure ..

power transformations ( like logs ) are not visually obvious .

Only your data knows what else is needed .

This question is similar to yours (they had 90 days ...you have 30 days ) Robust time-series regression for outlier detection . The whole idea is to build a model for the daily totals and then use daily total as a predictor variable for each of the 24 hourly models.

This question is similar to yours (they had 90 days ...you have 30 days ) Robust time-series regression for outlier detection . The whole idea is to build a model for the daily totals and then use daily total as a predictor variable for each of the 24 hourly models.

edit after a (visual) review of your data ..it is clear that have fixed daily effects and fixed hourly effects and outliers and a level shift (down) ... that having been said there may also be some arima structure ..

Only your data knows what else is needed .

This question is similar to yours (they had 90 days ...you have 30 days ) Robust time-series regression for outlier detection . The whole idea is to build a model for the daily totals and then use daily total as a predictor variable for each of the 24 hourly models.

This question is similar to yours (they had 90 days ...you have 30 days ) Robust time-series regression for outlier detection . The whole idea is to build a model for the daily totals and then use daily total as a predictor variable for each of the 24 hourly models.