1440 but the other variables are assigned values for my simulation. I'm having a hard time finding the suitable regression method which allows me to find the expression for the parameter expressed by the variables.If someone could point me toward the right direction that would be much ...
When observations in large data sets are aggregated into smaller more manageable data sizes, the resulting classifications of observations invariably involve symbolic data. In this paper, covariance and correlation functions are introduced for interval-valued symbolic data. These and their associated terms...
Identification of genes required for cellulose synthesis by regression analysis of public microarray data sets Coexpression patterns of gene expression across many microarray data sets may reveal networks of genes involved in linked processes. To identify factors in... S Persson,H Wei,J Milne,... ...
(2012). Confidence sets in a linear regression model for interval data. Journal of Statistical Planning and Inference, 142, 1320-1329.Blanco-Fernández, A., Colubi, A., González-Rodríguez, G.: Confidence sets in a linear regression model for interval data. J. Statist. Planning Infer. ...
Bank transactions are highly confidential. As a result, there are no real public data sets that can be used to investigate and compare anti-money laundering (AML) methods in banks. This severely limits research on important AML problems such as efficienc
This idea of “out-of-sample” validation is not new, but it did not really take hold until larger data sets became more prevalent; with a small data set, analysts typically want to use all the data and fit the best possible model. Using a holdout sample, though, leaves you subject ...
Data mining is the use of machine learning and statistical analysis to uncover patterns and other valuable information from large data sets.
Incomplete covariate data arise in many data sets. When the missing covariates are categorical, a useful technique for obtaining parameter estimates is the... Lipsitz,S. - 《Biometrika》 被引量: 227发表: 1996年 Regression analysis of incomplete medical cost data The accumulation of medical cost ...
A power trendline is a curved line that is best used with data sets that compare measurements that increase at a specific rate — for example, the acceleration of a race car at one-second intervals. You cannot create a power trendline if your data contains zero or negative ...
Using the expectation and the variance of fuzzy random variables, we consider a linear regression problem and limit theorems. Keywords: Probability theory ... R Rner - 《Fuzzy Sets & Systems》 被引量: 278发表: 1997年 Estimating smooth structural change in cointegration models The reason for thi...