Brazell, Jeff.
The SoV probit a probit model with structured covariance for similarity effects and source of volume calculations / [electronic resource] : Jeff Brazell. - London : Henry Stewart Talks, 2010. - 1 online resource (1 streaming video file (41 min.) : color, sound). - Bayesian analysis in marketing : a breakthrough in customer analytics, 2056-4570 . - Henry Stewart talks. Business & management collection. Bayesian analysis in marketing. .
Animated audio-visual presentation with synchronized narration. Title from title frames.
Contents: Source of volume and cannibalization -- Product and line optimization questions -- Quick definitions -- Red bus / blue bus example -- What is IID? and IIA? -- We know IIA/IID gets source-of-volume wrong -- When should we care about substitution patterns? -- Source of volume calculations -- Cannibalization = Preference -- How do you handle IIA in your choice models? -- Simulating preference shares: state-of-the-art -- What does proportional substitution look like? -- Industry survey: how do current methods do? -- The SoV Probit -- Why should I care about correlated errors? -- Why aren't we all using Probit models? -- A structured covariance Probit -- Distance metrics -- Choice experiment -- Model fit statistics -- Parameter estimates -- WTP comparison -- Representative correlation matrix -- Does it work?
Access restricted to subscribers.
Mode of access: World Wide Web.
2678 Henry Stewart Talks
Marketing.
Probits.
The SoV probit a probit model with structured covariance for similarity effects and source of volume calculations / [electronic resource] : Jeff Brazell. - London : Henry Stewart Talks, 2010. - 1 online resource (1 streaming video file (41 min.) : color, sound). - Bayesian analysis in marketing : a breakthrough in customer analytics, 2056-4570 . - Henry Stewart talks. Business & management collection. Bayesian analysis in marketing. .
Animated audio-visual presentation with synchronized narration. Title from title frames.
Contents: Source of volume and cannibalization -- Product and line optimization questions -- Quick definitions -- Red bus / blue bus example -- What is IID? and IIA? -- We know IIA/IID gets source-of-volume wrong -- When should we care about substitution patterns? -- Source of volume calculations -- Cannibalization = Preference -- How do you handle IIA in your choice models? -- Simulating preference shares: state-of-the-art -- What does proportional substitution look like? -- Industry survey: how do current methods do? -- The SoV Probit -- Why should I care about correlated errors? -- Why aren't we all using Probit models? -- A structured covariance Probit -- Distance metrics -- Choice experiment -- Model fit statistics -- Parameter estimates -- WTP comparison -- Representative correlation matrix -- Does it work?
Access restricted to subscribers.
Mode of access: World Wide Web.
2678 Henry Stewart Talks
Marketing.
Probits.