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  "Title": "Rank and Factor Loadings Estimation in Time Series Tensor Factor\nModels",
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  "Description": "A set of functions to estimate rank and factor loadings of\ntime series tensor factor models. A tensor is a\nmultidimensional array. To analyze high-dimensional tensor time\nseries, factor model is a major dimension reduction tool.\n'TensorPreAve' provides functions to estimate the rank of core\ntensors and factor loading spaces of tensor time series. More\nspecifically, a pre-averaging method that accumulates\ninformation from tensor fibres is used to estimate the factor\nloading spaces. The estimated directions corresponding to the\nstrongest factors are then used for projecting the data for a\npotentially improved re-estimation of the factor loading spaces\nthemselves. A new rank estimation method is also implemented to\nutilizes correlation information from the projected data. See\nChen and Lam (2023) <arXiv:2208.04012> for more details.",
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        "Pre-averaging procedure to estimate the strongest factor",
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