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.

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.

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).

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).

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.

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.

Abstract: A computer-implemented fraud detection method and system for periodically identifying network associations in a consumer population at a national credit reporting agency and computing associated network level variables related to credit use and potential first party fraud for the consumer population. In response to receiving a request for a target account from among the consumer population the computer-implemented system retrieves credit report for the target account and computes tradeline or account level variables related to credit use and potential fraudulent behavior. A fraud score is calculated based on a combined evaluation of the network level variables and the tradeline or account level variables.

Abstract: In a method of ranking or filtering new content items for presentation to members of a group of users of a social-networking service, content items that are candidates for presentation to the members are received. A user of the social-networking service is enabled to serve as a curator of the candidates, with the enabling including enabling the user to scroll through subsets of the candidates in a carousel user interface to indicate an opinion of the user with respect to an importance to the group of each of one or more candidates. One or more of the candidates are presented to the members of the group based on the opinion of the user with respect to the candidates.

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.

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.

Abstract: In a method of ranking or filtering new content items for presentation to members of a group of users of a social-networking service, content items that are candidates for presentation to the members are received. A user of the social-networking service is enabled to serve as a curator of the candidates, with the enabling including enabling the user to scroll through subsets of the candidates in a carousel user interface to indicate an opinion of the user with respect to an importance to the group of each of one or more candidates. One or more of the candidates are presented to the members of the group based on the opinion of the user with respect to the candidates.

Abstract: In a method of ranking or filtering new content items for presentation to members of a group of users of a social-networking service, content items that are candidates for presentation to the members are received. A user of the social-networking service is enabled to serve as a curator of the candidates, with the enabling including enabling the user to scroll through subsets of the candidates in a carousel user interface to indicate an opinion of the user with respect to an importance to the group of each of one or more candidates. One or more of the candidates are presented to the members of the group based on the opinion of the user with respect to the candidates.

Abstract: A computer system is provided for improved workforce management including: (A) one or more base stations including a base unit, an enclosure for a tablet computer, the enclosure being connectable to the base unit, the tablet computer including one or more utilities; and (B) a server computer linked to the one or more base stations; the server computer including a server application; wherein the base stations are configured to function both as a (i) multi-user workforce management base station, which may be a stationary base station (whether mounted on a wall or laid on a table for example) and (ii) a mobile device, detachable from the base station, that may be used for one or more enterprise defined operations, and access one or more workforce management utilities, implemented. An enclosure and base unit design is provided for the base station. Applications for extending the functionality of the computer system are also provided, as well as workforce management methods.

Abstract: A system and method for communicating status of individual patients to selected populations of residents include a computing platform, a database in communication with the computing platform, first, second, and third electronic communication devices used by patients, physicians and recipients respectively, and a software algorithm residing on the computing platform, controlled by the patient using the first communication device for implementing communications and patient status to the recipients.

Abstract: In a method of ranking or filtering new content items for presentation to members of a group of users of a social-networking service, content items that are candidates for presentation to the members are received. A user of the social-networking service is enabled to serve as a curator of the candidates, with the enabling including enabling the user to scroll through subsets of the candidates in a carousel user interface to indicate an opinion of the user with respect to an importance to the group of each of one or more candidates. One or more of the candidates are presented to the members of the group based on the opinion of the user with respect to the candidates.

Abstract: A contact list search with autocomplete is described. The contact list search searches on all contact information fields, including name, email, address, company, and so forth. The search results are updated on the fly as additional characters are entered to form new query strings. When a contact is selected from the results, a profile for a contact is displayed, including text boxes for editing the profile.

Abstract: Email and chat messages may be displayed as part of the same conversation, in an integrated conversation view. The conversation view would include items corresponding to email messages that are part of the conversation and chat messages that are part of the conversation. A user may reply to an email message in the conversation by chat.

Abstract: Participants in a chat session can control the archiving of chat messages in the chat session. Participants in a chat session send and receive a first set of chat messages, which are archived. A command to deactivate archiving is made by one of the participants. Messages in the chat session that are sent and received subsequent to the command to deactivate archiving are not archived. Archiving may be reactivated and messages subsequent to the command to reactivate archiving are archived.

Abstract: Methods and structures for providing a simulated rock speaker cabinet are disclosed herein. A simulated rock speaker includes a hollow casing having an interior surface, an exterior surface, and at least one port extending through and between the interior and exterior surfaces. A substantially even bottom edge forms a boundary around an open end of the hollow casing, and a speaker mounting assembly is coupled to the interior surface and substantially aligned with the at least one port. The exterior surface of the simulated rock speaker cabinet has an irregular finish simulating the configuration of a natural rock. A speaker coupled to the speaker mounting assembly aligns with the port to produce high quality sound without utilizing a visible grill in the exterior surface.