autocorrelated
Past predicts present
Autocorrelated describes data in which values are correlated with their own past values—each observation relates statistically to those that came before it.
Stock prices, temperature readings, and other time-series data are typically autocorrelated: The residuals were autocorrelated, violating the regression assumptions.
The phenomenon complicates statistical analysis because observations aren't independent.
Period of falling behind
- ARIMATime series forecasting model
- differencingComputing sequential differences
- forecastingEstimating future conditions
- trendDirection of change
Ongoing compensation for rebroadcasts
- inefficiencySuboptimal use of resources
- violationBreaking of rules
Unwanted auditory disturbance
Forming concentrated groups
- neighborhoodResidential area nearby
- contiguityState of touching directly
- hotspotArea of notable activity
lag
Period of falling behind
- ARIMATime series forecasting model
- differencingComputing sequential differences
- forecastingEstimating future conditions
residuals
Ongoing compensation for rebroadcasts
- inefficiencySuboptimal use of resources
- violationBreaking of rules
noise
Unwanted auditory disturbance
clustering
Forming concentrated groups
- neighborhoodResidential area nearby
- contiguityState of touching directly
- hotspotArea of notable activity
autocorrelateduncorrelated
Lacking statistical relationship
independent · white noise · random · memoryless · orthogonal
autocorrelatedrandom
Occurring without pattern
stochastic · unpatterned · structureless · patternless · unsystematic