TY - CHAP
T1 - Modelling Conditional Probability Distributions for Periodic Variables
AU - Bishop, Christopher
AU - Nabney, IanT.
PY - 1997
Y1 - 1997
N2 - Most conventional techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we introduce three related techniques for tackling such problems, and test them using synthetic data. We then apply them to the problem of extracting the distribution of wind vector directions from radar scatterometer data.
AB - Most conventional techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we introduce three related techniques for tackling such problems, and test them using synthetic data. We then apply them to the problem of extracting the distribution of wind vector directions from radar scatterometer data.
U2 - 10.1007/978-1-4615-6099-9_17
DO - 10.1007/978-1-4615-6099-9_17
M3 - Chapter
SN - 978-1-4613-7794-8
T3 - Operations Research/Computer Science Interfaces Series
SP - 118
EP - 122
BT - Mathematics of Neural Networks
A2 - Ellacott, StephenW.
A2 - Mason, JohnC.
A2 - Anderson, IainJ.
PB - Springer US
ER -