linear time series
Concentration inequalities for empirical processes of linear time series
... The paper considers suprema of empirical processes for linear time series indexed by func- tional classes. We derive an upper bound for the tail probability of the suprema under conditions on the ...
46
Generalized linear time series regression
... age, time and cohort effects in labour force participation by ...eralized linear time series model using a probit or logit link ...the time series of labour force participation ...
9
Non linearities in macroeconomics : evaluation of non linear time series models
... 2 Non-linear time series models have been applied to characterise, for example: i business cycle asymmetries Hamilton, 1989; Beaudry and Koop, 1993; Potter, 1995; ii asymmetries in the e[r] ...
263
Identification, Estimation and Specification in a Class of Semi Linear Time Series Models
... semiparametric time series model of the form (1.2). In model (1.1), the linear component in many cases plays the leading role while the nonparametric component behaves like a type of unknown ...
21
Non-Linear Time Series Modelling with Applications to Equity and Fixed Income Markets
... the linear alternative based on Hansen (1996) and Hansen (1997) inference procedures and this result is robust across all the stocks in my ...over time when the model stay in a particular regime ...
131
Estimation and identification for vector linear time series models
... where we allow identities to be present in (1.10). As far as Econometric applications are concerned, the most important ARMAX identification results have been given by Hannan in a series of papers, Hannan [1969a, ...
294
Inference problems for vector linear time series models
... of time series (and more specifically prediction theory) uncorrelated processes form a basic building block in the representation of a vide range of stationary ...
155
Estimation for vector linear time series models
... 13 1 - 1-6 are required in order that Whittle’s conditions hold. (Note that the proof of Theorem 3 in Whittle (1961) is incorrect since it is not true that the variance of NG(l) is 0(N) (see equation (8), p. 5 of ...
214
Recursive estimation of non-linear time series models
... A r.ecursive scheme for simultaneous optimal estimation of conditional mean and variance in a nonlinear ARCH (autoregressive con- ditional heteroscedastic) model is also proposed.. Keywo[r] ...
17
Automated classification of Persistent Scatterers Interferometry time series
... (PSI) time se- ries based on a conditional sequence of statistical tests. Time series are classified into distinctive predefined target trends, such as uncorrelated, linear, quadratic, ...
14
Study the Trend Pattern in COVID-19 using Spline-Based Time Series Model: A Bayesian Paradigm
... COVID-19 series in various countries is not linear because there are many reasons such as lockdown, infection modes, poor health infrastructure that control or expand this disease in the ...
13
Cybersecurity: Time Series Predictive Modeling of Vulnerabilities of Desktop Operating System Using Linear and Non Linear Approach
... non linear components of vulnera- ...on linear and non-linear approaches via time series ...Utilizing time series approach, this study has developed a predictive analytic ...
21
Modeling the Effects of Outliers on the Estimation of Linear Stochastic Time Series Model
... the linear time series models cannot be overemphasized; such effects range from false inference, introduction of biases in the model parameters, model misspecification and misleading confidence ...
18
Warming in Turkish Seas: Comparative Multidecadal Assessment
... selected time period, our analysis indicated that two groups occurred in the Turkish seas: one being the Black Sea and the Marmara Sea, and the other being the Aegean Sea and the Levantine ...recent linear ...
7
Estimation of semiparametric econometric time series models with non linear or heteroscedastic disturbances
... Assuming that ut is stationary and independent of all the xt, Hannan (1963) proposed an estimate of 0 that has the same asymptotic efficiency as the best linear unbiased estimate, without employing a parametric ...
224
Forecasting Inflation using Functional Time Series Analysis
... Each series of disaggregated data as a functional ...data series to get next level se- ries using some weights and finally getting ...the series after ...
28
A new data driven model for post transplant antibody dynamics in high risk kidney transplantation
... antibody time series and their diverse patterns have made the task of modelling ...39 time series from two groups of graft recipients, ...episodes. Linear and nonlinear dynamic models ...
10
Multigraded linear series and recollement
... In this section we recall Van den Bergh’s notion of an NCCR [35] and show that the moduli spaces determined by 0-generated stability parameters are multigraded linear series. We establish a set of ...
31
BEST LINEAR UNBIASED ESTIMATE USING BUYS-BALLOT PROCEDURE WHEN TREND-CYCLE COMPONENT IS LINEAR
... The second example is the 32 consecutive quarters of U.S beer production, in millions of barrels, from first quarter of 1975 to the fourth quarter of 1982, and is listed as Series W10 in Wei (1990). In order to ...
16
Time Series Analysis of PM10 for Bulandhshahr Industrial Area in NCR using Multiple Linear Regression
... Time series analysis is conducted for prediction of value of PM10 for Bulandhshahr industrial area in NCR of ...Multiple linear regression is used to formulate time series ...
7