Pages that link to "Item:Q1209877"
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The following pages link to Quadratic negligibility and the asymptotic normality of operator normed sums (Q1209877):
Displaying 16 items.
- Quasi-maximum likelihood estimators in generalized linear models with autoregressive processes (Q477916) (← links)
- Functional central limit theorems for self-normalized least squares processes in regression with possibly infinite variance data (Q645604) (← links)
- Large sample properties of mixture models with covariates for competing risks (Q700137) (← links)
- On the quasidiagonality of direct sums of normal operators and shifts (Q806005) (← links)
- QML estimators in linear regression models with functional coefficient autoregressive processes (Q980670) (← links)
- Functional asymptotic confidence intervals for the slope in linear error-in-variables models (Q1046876) (← links)
- Asymptotics for multivariate \(t\)-statistic for random vectors in the generalized domain of attraction of the multivariate normal law (Q1126116) (← links)
- Probabilistic characterizations of the generalized domain of attraction of the multivariate normal law (Q1337954) (← links)
- Random deletion does not affect asymptotic normality or quadratic negligibility (Q1372222) (← links)
- Estimation for a longitudinal linear model with measurement errors (Q1952067) (← links)
- Pseudo-maximum likelihood estimators in linear regression models with fractional time series (Q2066515) (← links)
- Invariance principles for a multivariate Student process in the generalized domain of attraction of the multivariate normal law (Q2231037) (← links)
- Matrix normalized convergence of a Lévy process to normality at zero (Q2342397) (← links)
- Maximum likelihood estimators in linear regression models with Ornstein-Uhlenbeck process (Q2405678) (← links)
- Asymptotics of regressions with stationary and nonstationary residuals. (Q2574563) (← links)
- Convergence to zero and boundedness of operator-normed sums of random vectors with application to autoregression processes (Q2761588) (← links)
