I have n=61 and t=25, and I have performed linear interpolation for missing values. Could it be the reason for insignificant GMM results? Please help.
Muhammad Amin Hasan
Yes, interpolation and extrapolation can affect the results of Gaussian Mixture Models (GMM).
Interpolation refers to predicting values within the range of the training data, while extrapolation refers to predicting values outside the range of the training data.
When GMM is used for interpolation, it assumes that the data within the range of the training data is generated from a mixture of Gaussian distributions. If this assumption is correct, then GMM can accurately predict the values within the range of the training data.
However, if the assumption is incorrect, then the predicted values may not accurately reflect the underlying distribution of the data.
Similarly, when GMM is used for extrapolation, it assumes that the data outside the range of the training data is generated from a mixture of Gaussian distributions. If this assumption is incorrect, then the predicted values may not be reliable.
Therefore, it is important to evaluate the assumptions made by GMM and carefully consider the implications of interpolation and extrapolation when interpreting the results.
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