PCE: Excluding Food & Energy - Chain Type Price Index - Not Seas Adj

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Automated Data Profiling

Ready Signal automatically profiles each data set and offers up suggested industry standard data science treatments to utilize with these data in your models.

Suggested Treatment:

The data shows auto correlation and seasonality. The data should be differenced and seasonally adjusted.

Grain Transformation:

Data is unable to be distributed by time or geography. The roll up method used is Weighted Average.

Auto Correlation Analysis:

Data shows auto correlation indicating a need for differencing

The ACF indicates 1 order differencing is appropriate.

Following first order differencing, no further differencing is required based on the differenced ACF at lag one of -0.07

Trend Analysis:

The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.15 p-value = 0.05 indicates that the data is not stationary.

Distribution Analysis:

The Shapiro-Wilk test returned W = 0.97 with a p-value =0.90 indicating the data follows a normal distribution.

A skewness score of 0.31 indicates the data are fairly symmetrical.

Hartigan's dip test score of 0.06 with a p-value of 0.99 inidcates the data is unimodal

Statistics (Pearson P/ df, lower => more normal)

No transform

0.27

Box-cox

0.27

Log_b(x-a)

0.27

sqrt(x+a)

0.27

exp(x)

13.07

arcsinh(x)

0.27

Yeo-Johnson

0.27

OrderNorm

0.27

Auto Correlation Function

Auto Correlation Function After Differencing

Partial Auto Correlation Function

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