Title
A Multipletesting Approach To The Multivariate Behrensfisher Problem: With Simulations And Examples In Sas (Springerbriefs In ,Used
Sold by Ergodebooks, an authorized reseller.
Returns accepted within 30 days | support@ergodebooks.com
Shipping Information
- Free Standard Shipping — United States only
- Processing Time: 1–3 business days
- Estimated Delivery: 3–5 business days after dispatch
- Double-boxed, fully insured & discreetly packaged
- Tracking number sent via email once dispatched
- Orders over $250 require signature upon delivery. Taxes calculated at checkout.
Returns & Refund
Returns accepted within 30 days of delivery.
Damaged or Defective Item
Free return shipping + replacement or full refund
Wrong Item Received
Free return shipping + replacement or full refund
Change of Mind
Return shipping at customer's expense · 25% restocking fee applies
Payment Option
In statistics, the BehrensFisher problem is the problem of interval estimation and hypothesis testing concerning the difference between the means of two normally distributed populations when the variances of the two populations are not assumed to be equal, based on two independent samples. In his 1935 paper, Fisher outlined an approach to the BehrensFisher problem. Since highspeed computers were not available in Fishers time, this approach was not implementable and was soon forgotten. Fortunately, now that highspeed computers are available, this approach can easily be implemented using just a desktop or a laptop computer. Furthermore, Fishers approach was proposed for univariate samples. But this approach can also be generalized to the multivariate case. In this monograph, we present the solution to the aforementioned multivariate generalization of the BehrensFisher problem. We start out by presenting a test of multivariate normality, proceed to test(s) of equality of covariance matrices, and end with our solution to the multivariate BehrensFisher problem. All methods proposed in this monograph will be include both the randomlyincompletedata case as well as the completedata case. Moreover, all methods considered in this monograph will be tested using both simulations and examples.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.