Estimasi Koefisien Acak Model Vektor Autoregresi

dc.contributor.advisor	Sutarman, Sutarman
dc.contributor.advisor	Mawengkang, Herman
dc.contributor.author	Rusdi, Ibnu
dc.date.accessioned	2022-11-11T07:42:17Z
dc.date.available	2022-11-11T07:42:17Z
dc.date.issued	2007
dc.identifier.uri	https://repositori.usu.ac.id/handle/123456789/58396
dc.description.abstract	The Least Absolute Value (LAV) has long been viewed as an attractive to OLS regression, however, in contract with OLS regression, there are so formulas for estimating the slope and intercept the LAV regression line. Several algorithm exist for these estimate in particular, the linear (goal) programming approach has received much attention. Regression lines estimated by ordinary least square are more severely affected by outliner or extreme data points, than those estimated with the LAV model	en_US
dc.language.iso	id	en_US
dc.publisher	Universitas Sumatera Utara	en_US
dc.title	Estimasi Koefisien Acak Model Vektor Autoregresi	en_US
dc.type	Thesis	en_US
dc.identifier.nim	NIM057021008
dc.identifier.nidn	NIDN0026106305
dc.identifier.nidn	NIDN8859540017
dc.identifier.kodeprodi	KODEPRODI44101#Matematika
dc.description.pages	31 Halaman	en_US
dc.description.type	Tesis Magister	en_US