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Stochastic Models for Geodesy and Geoinformation Science

Resumen/Descripción – provisto por la editorial

No disponible.

Palabras clave – provistas por la editorial

EM-algorithm; multi-GNSS; PPP; process noise; observation covariance matrix; extended Kalman filter; machine learning; GNSS phase bias; sequential quasi-Monte Carlo; variance reduction; autoregressive processes; ARMA-process; colored noise; continuous process; covariance function; stochastic modeling; time series; elementary error model; terrestrial laser scanning; variance-covariance matrix; terrestrial laser scanner; stochastic model; B-spline approximation; Hurst exponent; fractional Gaussian noise; generalized Hurst estimator; very long baseline interferometry; sensitivity; internal reliability; robustness; CONT14; Errors-In-Variables Model; Total Least-Squares; prior information; collocation vs. adjustment; mean shift model; variance inflation model; outlierdetection; likelihood ratio test; Monte Carlo integration; data snooping; GUM analysis; geodetic network adjustment; stochastic properties; random number generator; Monte Carlo simulation; 3D straight line fitting; total least squares (TLS); weighted total least squares (WTLS); nonlinear least squares adjustment; direct solution; singular dispersion matrix; laser scanning data

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Información

Tipo de recurso:

libros

ISBN electrónico

978-3-03943-982-9

País de edición

Suiza