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Through incremental integration and independent research and development, build a method library of big data quality control, automatic modeling and analysis, data mining and interactive visualization, form a tool library with high reliability, high scalability, high efficiency and high fault tolerance, realize the integration and sharing of collaborative analysis methods of multi-source heterogeneous, multi-granularity, multi-phase, long-time series big data in three pole environment, as well as high Efficient and online big data analysis and processing.

  • CoKriging

    CoKriging is a multivariate variant of the Ordinary Kriging operation: CoKriging calculates estimates or predictions for a poorly sampled variable (the predictand) with help of a well-sampled variable (the covariable)

    Installation: online;

    Dependent libraries: gstat ;

    QR code:

    2019-10-12 327 View Details

  • Regression Kriging

    Regression-kriging (RK) is a spatial prediction technique that combines a regression of the dependent variable on auxiliary variables (such as parameters derived from digital elevation modelling, remote sensing/imagery, and thematic maps) with kriging of the regression residuals

    Installation: online;

    Dependent libraries: gstat ;

    QR code:



    2019-10-12 314 View Details

  • Ordinary Kriging

    Ordinary kriging is the most widely used kriging method. It serves to estimate a value at a point of a region for which a variogram is known, using data in the neighborhood of the estimation location.

    Installation: online;

    Dependent libraries: gstat ;

    QR code:



    2019-10-12 230 View Details

  • Indicator Kriging

    Indicator kriging uses indicator (0 or 1) variables to generate probabilities that a critical value was exceeded or not at each location in the study area.

    Installation: online;

    Dependent libraries: gstat ;

    QR code:



    2019-10-12 234 View Details

  • Simple Kriging

    Simple kriging is mathematically the simplest, but the least general.It assumes the expectation of the random field to be known.

    Installation: online;

    Dependent libraries: gstat ;

    QR code:



    2019-10-12 214 View Details

  • Universal Kgiring

    Universal kriging assumes a general polynomial trend model, such as linear trend model, and simultaneously estimates a trend and uses the resulting errors for kriging.

    Installation: online;

    Dependent libraries: gstat ;

    QR code:



    2019-10-12 265 View Details

  • GeoStatistical Least Power Estimation

    GSLPE is a least power estimation based on geostatistics (Ordinary Kriging, etc.) and generalized Gaussian distribution. GSLPE has good accuracy, stability and robustness for the disorganized measurements with spatial heterogeneity, and is customized to the studies on upscaling for multi-point measurements.

    Installation: no installation required;

    The third-party toolkit: LAPACK、IT++、armadillo

    QR code:

    2019-10-17 272 View Details

  • CoKriging with Truncated Power Variogram

    CKT is a cokriging algorithm in conjunction with truncated power variogram, which has the ability to represent multiscale overlapping random fields. CKT specializes in capturing the multi-scale behavior of a geophysical variable ranging from the point scale to large windows, and its estimates are explicitly related to the magnitude of the scale. CKT performs better in a heavy-tailed distribution.

    Installation :no installation required;

    QR code:

    2019-10-17 262 View Details

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