Lectures on Algebraic Statistics
āĻāĻĒā§ā§°āĻŋāĻ˛ ā§¨ā§Ļā§Ļā§¯ ¡ Oberwolfach Seminars āĻāĻŋāĻ¤āĻžāĻĒ 39 ¡ Springer Science & Business Media
āĻāĻŦā§āĻ
172
āĻĒā§āĻˇā§āĻ āĻž
reportāĻŽā§āĻ˛ā§āĻ¯āĻžāĻāĻāĻ¨ āĻā§°ā§ āĻĒā§°ā§āĻ¯āĻžāĻ˛ā§āĻāĻ¨āĻž āĻ¸āĻ¤ā§āĻ¯āĻžāĻĒāĻ¨ āĻā§°āĻž āĻšā§ā§ąāĻž āĻ¨āĻžāĻ  āĻ
āĻ§āĻŋāĻ āĻāĻžāĻ¨āĻ
āĻāĻ āĻāĻŦā§āĻāĻāĻ¨ā§° āĻŦāĻŋāĻˇā§ā§
How does an algebraic geometer studying secant varieties further the understanding of hypothesis tests in statistics? Why would a statistician working on factor analysis raise open problems about determinantal varieties? Connections of this type are at the heart of the new field of "algebraic statistics". In this field, mathematicians and statisticians come together to solve statistical inference problems using concepts from algebraic geometry as well as related computational and combinatorial techniques. The goal of these lectures is to introduce newcomers from the different camps to algebraic statistics. The introduction will be centered around the following three observations: many important statistical models correspond to algebraic or semi-algebraic sets of parameters; the geometry of these parameter spaces determines the behaviour of widely used statistical inference procedures; computational algebraic geometry can be used to study parameter spaces and other features of statistical models.
āĻāĻ āĻāĻŦā§āĻāĻāĻ¨āĻ āĻŽā§āĻ˛ā§āĻ¯āĻžāĻāĻāĻ¨ āĻā§°āĻ
āĻāĻŽāĻžāĻ āĻāĻĒā§āĻ¨āĻžā§° āĻŽāĻ¤āĻžāĻŽāĻ¤ āĻāĻ¨āĻžāĻāĻāĨ¤
āĻĒāĻĸāĻŧāĻžā§° āĻ¨āĻŋāĻ°ā§āĻĻā§āĻļāĻžā§ąāĻ˛ā§
āĻ¸ā§āĻŽāĻžā§°ā§āĻāĻĢâāĻ¨ āĻā§°ā§ āĻā§āĻŦāĻ˛ā§āĻ
Android āĻā§°ā§ iPad/iPhoneā§° āĻŦāĻžāĻŦā§ Google Play Books āĻāĻĒāĻā§ āĻāĻ¨āĻˇā§āĻāĻ˛ āĻā§°āĻāĨ¤ āĻ āĻ¸ā§āĻŦāĻ¯āĻŧāĻāĻā§āĻ°āĻŋāĻ¯āĻŧāĻāĻžā§ąā§ āĻāĻĒā§āĻ¨āĻžā§° āĻāĻāĻžāĻāĻŖā§āĻā§° āĻ¸ā§āĻ¤ā§ āĻāĻŋāĻāĻ āĻšāĻ¯āĻŧ āĻā§°ā§ āĻāĻĒā§āĻ¨āĻŋ āĻ¯'āĻ¤ā§ āĻ¨āĻžāĻĨāĻžāĻāĻ āĻ¤'āĻ¤ā§āĻ āĻā§āĻ¨ā§ āĻ
āĻĄāĻŋāĻ
'āĻŦā§āĻ āĻ
āĻ¨āĻ˛āĻžāĻāĻ¨ āĻŦāĻž āĻ
āĻĢāĻ˛āĻžāĻāĻ¨āĻ¤ āĻļā§āĻ¨āĻŋāĻŦāĻ˛ā§ āĻ¸ā§āĻŦāĻŋāĻ§āĻž āĻĻāĻŋāĻ¯āĻŧā§āĨ¤
āĻ˛ā§āĻĒāĻāĻĒ āĻā§°ā§ āĻāĻŽā§āĻĒāĻŋāĻāĻāĻžā§°
āĻāĻĒā§āĻ¨āĻŋ āĻāĻŽā§āĻĒāĻŋāĻāĻāĻžā§°ā§° ā§ąā§āĻŦ āĻŦā§āĻ°āĻžāĻāĻāĻžā§° āĻŦā§āĻ¯ā§ąāĻšāĻžā§° āĻā§°āĻŋ Google PlayāĻ¤ āĻāĻŋāĻ¨āĻž āĻ
āĻĄāĻŋāĻ
'āĻŦā§āĻāĻ¸āĻŽā§āĻš āĻļā§āĻ¨āĻŋāĻŦ āĻĒāĻžā§°ā§āĨ¤
āĻ-ā§°ā§āĻĄāĻžā§° āĻā§°ā§ āĻ
āĻ¨ā§āĻ¯ āĻĄāĻŋāĻāĻžāĻāĻ
Kobo eReadersā§° āĻĻā§°ā§ āĻ-āĻāĻŋā§āĻžāĻāĻšā§ā§° āĻĄāĻŋāĻāĻžāĻāĻāĻ¸āĻŽā§āĻšāĻ¤ āĻĒā§āĻŋāĻŦāĻ˛ā§, āĻāĻĒā§āĻ¨āĻŋ āĻāĻāĻž āĻĢāĻžāĻāĻ˛ āĻĄāĻžāĻāĻ¨āĻ˛âāĻĄ āĻā§°āĻŋ āĻ¸ā§āĻāĻā§ āĻāĻĒā§āĻ¨āĻžā§° āĻĄāĻŋāĻāĻžāĻāĻāĻ˛ā§ āĻ¸ā§āĻĨāĻžāĻ¨āĻžāĻ¨ā§āĻ¤ā§°āĻŖ āĻā§°āĻŋāĻŦ āĻ˛āĻžāĻāĻŋāĻŦāĨ¤ āĻ¸āĻŽā§°ā§āĻĨāĻŋāĻ¤ āĻ-ā§°āĻŋāĻĄāĻžā§°āĻ˛ā§ āĻĢāĻžāĻāĻ˛āĻā§ āĻā§āĻ¨ā§āĻā§ āĻ¸ā§āĻĨāĻžāĻ¨āĻžāĻ¨ā§āĻ¤ā§° āĻā§°āĻŋāĻŦ āĻāĻžāĻ¨āĻŋāĻŦāĻ˛ā§ āĻ¸āĻšāĻžāĻ¯āĻŧ āĻā§āĻ¨ā§āĻĻā§ā§°āĻ¤ āĻĨāĻāĻž āĻ¸āĻŦāĻŋāĻļā§āĻˇ āĻ¨āĻŋā§°ā§āĻĻā§āĻļāĻžā§ąāĻ˛ā§ āĻāĻžāĻāĻāĨ¤
