Abstract: Methods, apparatus, and systems are disclosed for determining census-level audience metrics across demographics.

Abstract: Methods, apparatus, and systems are disclosed for determining census-level audience metrics across demographics. An example apparatus disclosed herein includes a distribution parameter solver to initialize distribution parameter values for a probability of an individual within a demographic being included in a subscriber audience for the demographic and having a first average impression duration, the subscriber audience having a first subscriber audience size, a divergence parameter solver to determine divergence parameter values between (i) the subscriber audience size and the first impression duration and (ii) a census-level audience size and a second impression duration based on the initialized distribution parameter values, and a search space identifier to identify a search space within bounds based on a census-level total impression count and a census-level total impression duration, the search space to define a range including an equality constraint.

Abstract: Methods, systems, apparatus and articles of manufacture to determine causal effects are disclosed herein. An example apparatus includes a weighting engine to calculate a first set of weights corresponding to a first treatment dataset, a second set of weights corresponding to a second treatment dataset, and a third set of weights corresponding to a control dataset, the weighting engine to increase an operational efficiency of the apparatus by calculating the first set of weights, second set of weights, and third set of weights independently, a weighting response engine to calculate a first weighted response for the first treatment dataset, a second weighted response for the second treatment dataset, and determine a causal effect between the first treatment dataset and the second treatment dataset based on a difference between the first weighted response and the second weighted response, and a report generator to transmit a report to an audience measurement entity.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve multi-demographic modeling efficiency. An example apparatus includes a feature set aggregator to segregate training data based on feature sets of interest, and to identify households that participate in at least one of the feature sets of interest, a class enumerator to reduce multi-demographic model iterations by enumerating demographic combinations for the identified households, the enumerated demographic combinations including a single identifier to represent a combination of two or more demographic categories, and a modeling engine to generate training coefficients associated with respective ones of the enumerated demographic combinations.

Abstract: An example apparatus to determine census-based audience metrics of media across multiple demographics includes an audience size determiner to determine a first census-level audience size based on a third-party audience size, a third-party impression count, and a first cross-demographic total census parameter value; an impression counts determiner to determine a first census-level impression count based on the third-party audience size, the third-party impression count, and the first cross demographic total census parameter value; and a verifier to determine whether the first cross-demographic total census parameter value satisfies a constraint based on the first census-level impression count; and when the constraint is not satisfied the verifier to: (a) discard the first cross-demographic total census parameter value, and (b) select a second cross-demographic total census parameter value, the second cross-demographic total census parameter value to determine a second census-level audience size and a second ce

Abstract: Methods, systems, apparatus and articles of manufacture to determine causal effects are disclosed herein. An example apparatus includes a weighting engine to calculate a first set of weights for a first set of covariates corresponding to a treatment dataset and a second set of weights for a second set of covariates corresponding to a control dataset using maximum entropy, the first set of weights to equal the second set of weights.

Abstract: Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach for different unions based on marginal ratings. An example method includes performing first parallel computations to determine first multipliers corresponding to a total number of panelists exposed to media at (a) a first margin of time, (b) a second margin of time, and (c) a union corresponding to the first and second margins of time, keeping a subset of the first multipliers corresponding to unknown census data; performing second parallel computation to determine second multipliers corresponding to a total audience exposed to the media at the first margin of time and the second margin of time, the second parallel computations to be performed by solving second equations corresponding to a tree association; and determining an estimate for a population reach of the union based on the second multipliers.

Abstract: Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach for different unions based on marginal ratings. An example apparatus includes a reach determiner to determine a population reach estimate of a union of time intervals for which media ratings data is available, the population reach estimate based on a pseudo universe estimate of a population audience corresponding to the union of the time intervals; a pseudo universe determiner to determine a pseudo universe estimate of a recorded audience corresponding to the union of the time intervals; determine the pseudo universe estimate of the population audience based on the pseudo universe estimate of the recorded audience; and iteratively update the pseudo universe estimate of the population audience to reduce an error; and a consistency checker to adjust the population reach estimate, the reach determiner to output the population reach estimate of the union.

Abstract: Methods, systems, and apparatus for calibrating data using relaxed benchmarks constraints are described. An example apparatus for generating a unique solution when calibrating data via a calibration model having relaxed benchmark constraints includes a calibration engine to execute the calibration model based on a target loss function, a weight loss function, and a budget parameter. The example apparatus further includes a calibrated weights determiner to determine calibrated weights resulting from execution of the calibration model. The example apparatus further includes a calibration model validator to incorporate a stability parameter into the calibration model in response to determining that the calibrated weights do not provide a unique solution for the executed calibration model. The stability parameter is to reduce an influence of the budget parameter on the calibration model to enable the generation of a unique solution.

Abstract: Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach for different unions based on marginal ratings.

Abstract: Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach for different unions based on marginal ratings.

Abstract: Example methods, apparatus, and articles of manufacture are disclosed to estimate population reach. An example apparatus includes an association controller to generate a tree association corresponding to a union of a first margin of media and a second margin of the media; and one or more commercial solvers to determine first multipliers by solving first equations corresponding to panelist impressions and panelist audience totals, the second margin, or the union; perform first parallel computations with a processor to determine second multipliers to solve second equations corresponding to the tree association using the first multipliers; discard the first multipliers; perform second parallel computations to determine third multipliers by solving third equations corresponding to the tree association using database proprietor impression totals; and determine an estimate for a population reach of the media for at least one of the first margin, the second margin, or the union based on the third multipliers.

Abstract: Methods, systems and apparatus for calibrating data using relaxed benchmarks constraints are described. An example apparatus for generating a unique solution when calibrating data via a calibration model having relaxed benchmark constraints includes a calibration engine to execute the calibration model based on a target loss function, a weight loss function, and a budget parameter. The example apparatus further includes a calibrated weights determiner to determine calibrated weights resulting from execution of the calibration model. The example apparatus further includes a calibration model validator to incorporate a stability parameter into the calibration model in response to determining that the calibrated weights do not provide a unique solution for the executed calibration model. The stability parameter is to reduce an influence of the budget parameter on the calibration model to enable the generation of a unique solution.

Abstract: An example apparatus includes a misattribution matrix generator to generate a misattribution matrix based on panelist data corresponding to audience measurement panelists. The misattribution matrix representing a panelist media impression as misattributed to a first demographic group by a database proprietor when the panelist media impression corresponds to a second demographic group. The apparatus also includes a census distribution analyzer to determine, based on the misattribution matrix, probability values that different census distribution models correspond to a true census distribution for census media impressions indicated in a misattributed census distribution. The true census distribution indicating a distribution of the census media impressions across the first and second demographic groups and accounting for misattribution by the database proprietor in the misattributed census distribution.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to determine advertisement campaign effectiveness using covariate matching.

Abstract: Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach for different unions based on marginal ratings. An example apparatus includes a reach determiner to estimate a population reach of a union of time intervals for which media ratings data is available; a pseudo universe determiner to determine a pseudo universe estimate of a recorded audience corresponding to the union; determine a pseudo universe estimate of a population audience corresponding to the union based on the pseudo universe estimate of the recorded audience; and determine an error of the population reach estimate of the union based on the pseudo universe of the population audience corresponding to the union; and the reach determiner to when the error does not satisfy a threshold, adjust the population reach estimate; and when the error does satisfy the threshold, determine the population reach of the union based on the population reach estimate.

Abstract: An example apparatus includes a matrix processor in circuit with a probability generator to determine a first matrix representative of element-wise multiplication between a constraint matrix and a first transpose matrix of the estimated demographic impression distribution, the constraint matrix based on the reference demographic impression distribution and determine a second matrix by multiplying the first matrix with a second transpose matrix of the constraint matrix. The apparatus further includes an error determiner in circuit with the matrix processor, the error determiner to determine an error indicator value based on the second matrix, the error indicator value indicative of an error associated with the estimated demographic impression distribution, and a probability generator to generate, in response to the error indicator value satisfying a threshold, an accuracy-improved demographic impression distribution.

Abstract: Methods, systems and apparatus to improve the efficiency of calculating a customer retention rate are disclosed herein.

Abstract: Example methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to implement neural network processing of set-top box return path data to estimate household demographics are disclosed. Example demographic estimation systems disclosed herein include a feature generator to generate features from return path data reported from set-top boxes associated with return path data households. Disclosed example demographic estimation systems also include a neural network to process the features generated from the return path data to predict demographic classification probabilities for the return path data households, the neural network to be trained based on panel data reported from meters that monitor media devices associated with panelist household.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to to estimate population reach from marginal ratings. An example apparatus includes an interface to access marginal ratings of the media for a recorded audience, marginal ratings of the media for a population audience, and reach of the media for the recorded audience; a reach determiner to iteratively estimate a reach of the media for the population audience based on the marginal ratings for the recorded audience, the marginal ratings for the population audience, and the reach for the recorded audience; and the interface to output the estimated reach for the population audience.