Comparison o f the Univariate and Multivariate Optimisations
Multivariate models for pretest posttest data and a comparison to univariate models
... the univariate methods to the multivariate method, data was simulated under three di↵erent predefined ...the multivariate method were fitted to the ...
25
Comparison of univariate and multivariate linkage analysis of traits related to hypertension
... a univariate and multivariate linkage approach to analyze SBP or traits related to HTN (and highly correlated with SBP) - TG, LDL, and HDL, ...the univariate results ...
5
Univariate and multivariate Pareto models
... The survey presented in this paper is far from complete. A more detailed and extensive survey (though somewhat out of date) can be found in Arnold (1983). A revision of that book is, however, currently in preparation. In ...
16
Bias in Estimating Multivariate and Univariate Diffusions
... Abstract Multivariate continuous time models are now widely used in economics and ...linear multivariate continuous time systems that includes the commonly used Euler and trapezoidal approximations as ...
38
A Comparison of Univariate ARIMA and Multivariate to Estimate Absorption Pattern in Stronsium Tittanate Dop Variation
... two, univariate model and multivariate model. One example of univariate model is Autoregressive Integrated Moving Average ...The multivariate model observed more than one observational ...
5
Univariate and Multivariate Time Series Manifold Learning
... Time series analysis aims to extract meaningful information from data that has been generated in sequence by a dynamic process. The modelling of the non-linear dynamics of a signal is often performed using a linear space ...
18
A Univariate, Bivariate and Multivariate Extensions for the Inverse Rayleigh Model with Properties and Applications to the Univariate Version
... A new univariate extension of the Inverse Rayleigh distribution is proposed and studied. Some of its fundamental statistical properties such as some stochastic properties, ordinary and incomplete moments, moments ...
19
Shapelet Transforms for Univariate and Multivariate Time Series Classification
... by O(n 2 m 4 ...believe multivariate contracted ensembling is a large open ended research question, and worth significant exploration, but is out of the scope of this piece of ...
182
On the Univariate Representation of Multivariate Volatility Models with Common Factors
... some multivariate models accounting for co-movements and show that the implied marginal volatility processes are of low ...general multivariate framework, with correlated conditional variances and contagion ...
20
Essays on univariate and multivariate modeling of financial market risks
... While there are plenty of studies on the characteristics of financial time-series data in the econometrics literature, modeling internet search queries has not yet been suf- ficiently investigated. At the model ...
240
Univariate and multivariate ARIMA versus vector autoregression forecasting
... f o r e c a s t s . These models d i f f e r i n how t h e y model t h e r e l a t i o n s h i p s among t h e s e r i e s ...i o n s h i p s can be approximated by u s i n g ...
32
The effect of univariate bias adjustment on multivariate hazard estimates
... Whether univariate bias-adjustment methods effectively improve estimates of impacts that depend on multiple drivers is largely unknown, and the lack of long-term impact data prevents a direct comparison ...
13
Statistical Models and Analysis of Univariate and Multivariate Degradation Data
... and multivariate degradation processes, to the best of our knowledge, these bivariate or multivariate degra- dation models are studied only in a parametric framework in which a parametric form of the ...
180
Assessing Univariate and Multivariate Normality, A Guide For Non-Statisticians
... both univariate and multivariate normality, several methods have been ...the univariate setting, the Q-Q plot, histogram, box plot, stem-and-leaf plot or dot plot are some graphical methods that can ...
8
Univariate and Multivariate GARCH Models Applied to the CARBS Indices
... Abstract The purpose of this paper is to estimate the calibrated parameters of dif- ferent univariate and multivariate GARCH family models. It is unrealistic to assume that volatility of financial returns ...
16
The effect of univariate bias adjustment on multivariate hazard estimates
... Whether univariate bias-adjustment methods effectively improve estimates of impacts that depend on multiple drivers is largely unknown, and the lack of long-term impact data prevents a direct comparison ...
13
A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia
... that multivariate models provided more accurate fore- casts for ED demand than univariate models is consistent with the findings of Jones and colleagues [12] ...
12
Clusterers: a comparison of partitioning and density-based algorithms and a discussion of optimisations
... 2.3. Partitioning clustering algorithms Partitioning methods define clusters by grouping data points into k partitions, defined by the user at the time the process is executed. A point is determined to be similar to ...
14
A comparison of multivariate and univariate models for pre test post test data concerning accuracy in the presence of missing data
... a MV method offers various benefits and more reliable results in significance testing over the univariate methods. This study only compared the immediate results concerning accuracy, bias and pre- diction. Schafer ...
22
Univariate and multivariate control charts for monitoring sugar production process
... Usually, in industry, there are many situations in which the simultaneous monitoring or control in two or more related quality process characteristics is necessary. Monitoring these process variables independently can ...
13