Patents by Inventor Clayton Adam Barker

Clayton Adam Barker has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11361255
    Abstract: Graphical interactive model selection is provided. A response variable vector for each value of a group variable and an explanatory variable vector are defined. A wavelet function is fit to the explanatory variable vector paired with the response variable vector defined for each value of the group variable. Each fit wavelet function defines coefficients for each value of the group variable. A curve is presented for each value of the group variable and is defined by the plurality of coefficients of an associated fit wavelet function. An indicator is received of a request to perform functional analysis using the coefficients for each value of the of the group variable based on a predefined factor variable. A model is trained using the coefficients for each value of the group variable and a factor variable value associated with each observation vector of each plurality of observation vectors as a model effect.
    Type: Grant
    Filed: July 28, 2021
    Date of Patent: June 14, 2022
    Assignee: SAS Institute Inc.
    Inventors: Ryan Jeremy Parker, Clayton Adam Barker, Jeremy Ryan Ash, Christopher Michael Gotwalt
  • Publication number: 20210365842
    Abstract: Graphical interactive model selection is provided. A response variable vector for each value of a group variable and an explanatory variable vector are defined. A wavelet function is fit to the explanatory variable vector paired with the response variable vector defined for each value of the group variable. Each fit wavelet function defines coefficients for each value of the group variable. A curve is presented for each value of the group variable and is defined by the plurality of coefficients of an associated fit wavelet function. An indicator is received of a request to perform functional analysis using the coefficients for each value of the of the group variable based on a predefined factor variable. A model is trained using the coefficients for each value of the group variable and a factor variable value associated with each observation vector of each plurality of observation vectors as a model effect.
    Type: Application
    Filed: July 28, 2021
    Publication date: November 25, 2021
    Inventors: Ryan Jeremy Parker, Clayton Adam Barker, Jeremy Ryan Ash, Christopher Michael Gotwalt
  • Patent number: 11100395
    Abstract: An analytic system provides direct functional principal component analysis. (A) A next group variable value is selected from values of a group variable. (B) Explanatory variable values of observations having the selected next group variable value are sorted in ascending order. (C) The response variable value associated with each sorted explanatory variable value is stored in a next row of a data matrix. (D) (A) through (C) are repeated. (E) An eigenfunction index is incremented. (F) An FPCA is performed using the data matrix to define an eigenfunction for the eigenfunction index. (G) (E) and (F) are repeated. (H) FPCA results from the performed FPCA are presented within a window of a display. The FPCA results include an eigenvalue and an eigenfunction associated with the eigenvalue for each functional principal component identified from the performed FPCA in (F).
    Type: Grant
    Filed: January 26, 2021
    Date of Patent: August 24, 2021
    Assignee: SAS Institute Inc.
    Inventors: Ryan Jeremy Parker, Clayton Adam Barker, Christopher Michael Gotwalt
  • Publication number: 20210174207
    Abstract: An analytic system provides direct functional principal component analysis. (A) A next group variable value is selected from values of a group variable. (B) Explanatory variable values of observations having the selected next group variable value are sorted in ascending order. (C) The response variable value associated with each sorted explanatory variable value is stored in a next row of a data matrix. (D) (A) through (C) are repeated. (E) An eigenfunction index is incremented. (F) An FPCA is performed using the data matrix to define an eigenfunction for the eigenfunction index. (G) (E) and (F) are repeated. (H) FPCA results from the performed FPCA are presented within a window of a display. The FPCA results include an eigenvalue and an eigenfunction associated with the eigenvalue for each functional principal component identified from the performed FPCA in (F).
    Type: Application
    Filed: January 26, 2021
    Publication date: June 10, 2021
    Inventors: Ryan Jeremy Parker, Clayton Adam Barker, Christopher Michael Gotwalt
  • Patent number: 10970651
    Abstract: Graphical interactive model selection is provided. A dataset includes observation vectors defined for each value of a plurality of values of a group variable. A nonlinear model is trained with each plurality of observation vectors to describe the response variable based on the explanatory variable for each value of the plurality of values of the group variable. Nonlinear model results are presented within a first sub-window of a first window. An indicator of a request to perform parameter analysis of the nonlinear model results is received. A linear model is trained. Trained linear model results from the trained linear model are presented within a second sub-window of the first window for each parameter variable of the nonlinear model. Predicted response variable values are presented as a function of the explanatory variable and the factor variable value using the trained nonlinear model within a third sub-window of the first window.
    Type: Grant
    Filed: June 18, 2020
    Date of Patent: April 6, 2021
    Assignee: SAS Institute Inc.
    Inventors: Clayton Adam Barker, Ryan Jeremy Parker, Christopher Michael Gotwalt
  • Patent number: 10963788
    Abstract: Graphical interactive model selection is provided. A basis function is fit to each plurality of observation vectors defined for each value of a group variable. Basis results are presented within a first sub-window of a first window of a display. Functional principal component analysis (FPCA) is automatically performed on each basis function. FPCA results are presented within a second sub-window of the first window. An indicator of a request to perform functional analysis using the FPCA results based on a predefined factor variable is received in association with the first window. A model is trained using an eigenvalue and an eigenfunction computed as a result of the FPCA for each plurality of observation vectors using the factor variable value as a model effect. (G) Trained model results are presented within a third sub-window of the first window of the display.
    Type: Grant
    Filed: July 2, 2020
    Date of Patent: March 30, 2021
    Assignee: SAS Institute Inc.
    Inventors: Ryan Jeremy Parker, Clayton Adam Barker, Christopher Michael Gotwalt
  • Patent number: 9773211
    Abstract: A graphical display of values generated according to a penalized regression model for multiple parameters of a data set shows the values as a graph having a first axis that represents magnitude of multiple parameter estimates of the penalized regression model and having a second axis that represents parameter estimate values of the multiple parameters of the penalized regression model. A user input is received that comprises a change to a parameter handle of the graphical display and changes at least one data parameter of the penalized regression model. The graphical display is changed such that the graphical display shows a representation of the values for the penalized regression model in accordance with the changes.
    Type: Grant
    Filed: January 15, 2015
    Date of Patent: September 26, 2017
    Assignee: SAS Institute Inc.
    Inventor: Clayton Adam Barker
  • Publication number: 20150331963
    Abstract: A graphical display of values generated according to a penalized regression model for multiple parameters of a data set shows the values as a graph having a first axis that represents magnitude of multiple parameter estimates of the penalized regression model and having a second axis that represents parameter estimate values of the multiple parameters of the penalized regression model. A user input is received that comprises a change to a parameter handle of the graphical display and changes at least one data parameter of the penalized regression model. The graphical display is changed such that the graphical display shows a representation of the values for the penalized regression model in accordance with the changes.
    Type: Application
    Filed: January 15, 2015
    Publication date: November 19, 2015
    Inventor: Clayton Adam Barker