Surrogate data, sometimes known as analogous data, usually refers to

time series In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Exa ...

data that is produced using well-defined (linear) models like ARMA processes that reproduce various statistical properties like the

autocorrelation Autocorrelation, sometimes known as serial correlation in the discrete time case, is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations of a random variable ...

structure of a measured data set. The resulting surrogate data can then for example be used for testing for non-linear structure in the empirical data, see

surrogate data testing Surrogate data testing (or the ''method of surrogate data'') is a statistical proof by contradiction technique and similar to permutation tests and as a resampling technique related (but different) to parametric bootstrapping. It is used to detect ...

. Surrogate or analogous data may refer to data used to supplement available data from which a

mathematical model A mathematical model is a description of a system using mathematical concepts and language. The process of developing a mathematical model is termed mathematical modeling. Mathematical models are used in the natural sciences (such as physics, ...

is built. Under this definition, it may be generated (i.e.,

synthetic data Synthetic data is information that's artificially generated rather than produced by real-world events. Typically created using algorithms, synthetic data can be deployed to validate mathematical models and to train machine learning models. Data g ...

) or transformed from another source.

Uses

Surrogate data is used in environmental and laboratory settings, when study data from one source is used in estimation of characteristics of another source. For example, it has been used to model population trends in animal species. It can also be used to model biodiversity, as it would be difficult to gather actual data on all species in a given area. Surrogate data may be used in forecasting. Data from similar series may be pooled to improve forecast accuracy. Use of surrogate data may enable a model to account for patterns not seen in historical data. Another use of surrogate data is to test models for non-linearity. The term

refers to algorithms used to analyze models in this way. These tests typically involve generating data, whereas surrogate data in general can be produced or gathered in many ways.

Methods

One method of surrogate data is to find a source with similar conditions or parameters, and use those data in modeling. Another method is to focus on patterns of the underlying system, and to search for a similar pattern in related data sources (for example, patterns in other related species or environmental areas). Rather than using existing data from a separate source, surrogate data may be generated through statistical processes, which may involve random data generation using constraints of the model or system.

Uses

Methods

See also

References

Further reading