All Questions
Tagged with logarithm time-series
33
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How can I back transform the residuals of a decomposed time series , where I used log(x+c) transformation on the original data?
I did a time series decomposition on a series of Twitter activity data into trend, seasonal and residual component. I checked the distribution of the residuals when fitting a linear model to the time ...
- 41
1
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1
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62
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ARIMAX model for Google trends: trouble with lots of zeros
I want to apply ARIMAX model on Google trends. I used python package to get daily data. However, this data contains a lot of zeros, so if I do first difference of logs, I see a lot of (inf) in python.
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- 47
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34
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Can I transform variables to comply with conditions on order of integration in an ARDL model?
If log variable have a unit root, can you then difference it?
For ARDL model variables should not be I(2) or more. Variables of log form are I(2). Would it be a problem to difference it.
What I am ...
- 25
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Forecasting with log transformed data and then taking the exponential of my predictions [duplicate]
I am aware a similar question was asked here Interpreting forecast predictions of log transformed data.
But I would like a deeper comment/answer.
I have a time series and want to make forecast. I ...
- 113
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42
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Can log-transform to TS reduce forecast accuracy vs non-transformed TS
I have to apply a SARIMAX model to over 300 TS. Many of them have increasing volatility which can be addressed by aplying log to the TS.
Problem is that also many TSs don't have this problem. Is it ok ...
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2
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Anything wrong with taking the log of an interest rate?
Suppose I am looking to forecast the 2 Year Treasury Bond rate with an ARIMA type model. The series is I(1) but its first difference does not look stationary due to non-constant variance. A general ...
- 4,758
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64
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VECM terms of variables
I have estimated a VECM model of 4 endogenous variables and 3 exogenous, before solving my model, I would like to introduce another variable (endog, let's say (X)) which is calculated with a formula ...
2
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1
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Percentage change vs log change in a repeated measures or time series analysis
I'm trying to measure growth over 8 weeks between two groups.
In essence it's an 8 (week) x 2 (group) analysis.
What is the best practice, percent change in my dependent variable across weeks (e.g. ...
- 59
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40
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Identify non-linear trend to know when to use log transformation in ARIMA?
There are basically three often used approaches to make time series stable based on three difference scenarios: 1) first difference for linear trend; 2) log for non-linear trend; 3) log seasonal ...
2
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1
answer
165
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Differencing Time Series
I am trying to remove the trends by differencing this logarithmically transformed time series. It contains two columns about COVID-19 Cases in the United States: one column being the number of cases ...
- 504
-1
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1
answer
1k
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How to reverse log difference?
I am currently doing log differences to a dataset and I want to revert back to the actual values. I'm trying to understand why at the end we need to multiply by the original value (and why we do not ...
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2
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When is log-transformation appropriate in unit-root testing?
In applied work in economics when people perform unit-root tests on level variables they virtually always transform them first by using natural logarithms.
However, I wonder if this is always ...
- 905
3
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74
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why arima uses differencing transform not the log transform to make data stationary?
I am currently working on time series project and i am naive.
I would like to ask, there exist strict stationary, differencing stationarity.
If i understood correct the first order differencing ...
- 131
8
votes
1
answer
10k
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Shall we use log(diff(x)) or diff(log(x))?
I am starting to learn time series and when detrending I always end up with the same doubt...
Generally, I use diff() for, let's say there is an upward trend like ...
- 789
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35
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Detect anomaly users who try to access too often based on the access log
Does anyone give me advice for statistically detecting anomaly users who try to log in our website too often?
At first, the idea that came to my mind is to use Spike detection approaches or IQR ...
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