|
algal blooms |
4 |
|
bootstrap method |
4 |
|
early warning system |
4 |
|
garch |
4 |
|
garch model |
4 |
|
least absolute deviation |
4 |
|
likelihood ratio test |
4 |
|
long range dependence |
4 |
|
red-tide |
4 |
|
threshold model |
4 |
|
time series forecasting |
4 |
|
varx modelling |
4 |
|
ar(p) model |
3 |
|
asymptotic distribution |
3 |
|
autoregression |
3 |
|
barium - toxicity |
3 |
|
benchmarking |
3 |
|
benthic biodiversity |
3 |
|
bootstrap |
3 |
|
buffered ar model |
3 |
|
buffered ar(p) model |
3 |
|
buffered ar-garch model |
3 |
|
buffered threshold model |
3 |
|
cadmium - toxicity |
3 |
|
capital gain tax |
3 |
|
categorical time series |
3 |
|
cointegration |
3 |
|
conditional least squares |
3 |
|
diagnostic checking |
3 |
|
ecological modeling |
3 |
|
em algorithm |
3 |
|
empirical bayesian methods |
3 |
|
exchange rate |
3 |
|
fuzzy sets |
3 |
|
geometric ergodicity |
3 |
|
goodness-of-fit test |
3 |
|
gps trajectory data segmentation |
3 |
|
guidelines as topic |
3 |
|
hidden markov model |
3 |
|
hysteresis |
3 |
|
marked empirical process |
3 |
|
newton's method |
3 |
|
nonlinear time series |
3 |
|
numerical integral simulation |
3 |
|
pairs trading |
3 |
|
particle swarm optimization |
3 |
|
polycyclic hydrocarbons, aromatic - toxicity |
3 |
|
power statistic |
3 |
|
prediction of demand |
3 |
|
probabilistic logic |
3 |
|
qmle |
3 |
|
regime switching |
3 |
|
residual autocorrelation |
3 |
|
return maximization |
3 |
|
risk control |
3 |
|
sediment quality guidelines |
3 |
|
species sensitivity distribution |
3 |
|
steady-state probability distribution |
3 |
|
threshold ar model |
3 |
|
threshold ar(p) model |
3 |
|
vector autoregression |
3 |
|
volatility |
3 |
|
0167-6687 |
2 |
|
absolute residual autocorrelation |
2 |
|
acbve |
2 |
|
adjustment coefficient |
2 |
|
arch() |
2 |
|
arfima |
2 |
|
asymmetric innovation |
2 |
|
asymptotic distributions |
2 |
|
asymptotic normality |
2 |
|
asymptotic properties |
2 |
|
auto-regressive integrated moving average |
2 |
|
autoregressive conditional duration |
2 |
|
autoregressive conditional duration model |
2 |
|
autoregressive conditional duration models |
2 |
|
autoregressive moving average model |
2 |
|
barrier strategy |
2 |
|
basket trading |
2 |
|
bayesian estimation |
2 |
|
binomial expansion technique |
2 |
|
black-litterman |
2 |
|
block gibbs sampling |
2 |
|
block-wise random weighting method |
2 |
|
by-claim |
2 |
|
co-integration |
2 |
|
common shock |
2 |
|
compound binomial risk model |
2 |
|
compound poisson |
2 |
|
conditional correlation |
2 |
|
conditional heteroscedastic model |
2 |
|
conditional heteroscedasticity |
2 |
|
conditional means |
2 |
|
conditional quantile estimation |
2 |
|
conditionally heteroscedastic model |
2 |
|
conservation of natural resources |
2 |
|
correlated aggregate claims |
2 |
|
correlation stress testing |
2 |
|
covariance stationarity |
2 |
|
credit ratings |
2 |
|
credit risk |
2 |
|
data mining. |
2 |
|
default data |
2 |
|
delayed claims |
2 |
|
discrete-time risk model |
2 |
|
double autoregressive model |
2 |
|
dynamic model |
2 |
|
environmental monitoring |
2 |
|
environmental remediation |
2 |
|
environmental remediation - economics - methods - statistics and numerical data |
2 |
|
exchange rates |
2 |
|
expected discounted penalty function |
2 |
|
extreme value theory |
2 |
|
factor model |
2 |
|
feedback effect |
2 |
|
financial engineering. |
2 |
|
finite mixture model |
2 |
|
gaussian process |
2 |
|
gehan‐type rank statistics |
2 |
|
gerber–shiu function |
2 |
|
gramcharlier density |
2 |
|
hats |
2 |
|
heavy tail |
2 |
|
heterogeneity |
2 |
|
heterogeneous censoring |
2 |
|
hidden markov model (hmm) |
2 |
|
high-dimension |
2 |
|
high-frequency |
2 |
|
high‐dimensional survival data |
2 |
|
hyperbolic decay |
2 |
|
hyperbolic garch |
2 |
|
hyperbolic garch model |
2 |
|
hysteretic model |
2 |
|
insurance claims modeling |
2 |
|
integer-valued garch |
2 |
|
integrated covariance matrix |
2 |
|
integro-differential equation |
2 |
|
interactive hidden markov model (ihmm) |
2 |
|
intercorrelated |
2 |
|
intervention analysis |
2 |
|
invariant probability measure |
2 |
|
kurtosis |
2 |
|
lagrange multiplier test |
2 |
|
least squares estimation |
2 |
|
leptokurtic innovation |
2 |
|
linear programming |
2 |
|
linear regression |
2 |
|
local least absolute deviation estimator |
2 |
|
logistic mixture |
2 |
|
long memory |
2 |
|
long memory in volatility |
2 |
|
long-range dependence |
2 |
|
lundberg-type inequality |
2 |
|
ma-garch model |
2 |
|
mahalanobis distance |
2 |
|
main claim |
2 |
|
market microstructure |
2 |
|
markov analysis |
2 |
|
mgarch |
2 |
|
mixture arch(∞) |
2 |
|
mixture component testing |
2 |
|
mixture exponential distribution |
2 |
|
mixture model |
2 |
|
mixture time series |
2 |
|
mixtures |
2 |
|
model diagnostic checking |
2 |
|
models, theoretical |
2 |
|
multivariate autoregressive model |
2 |
|
multivariate portmanteau test |
2 |
|
multivariate tvcc model |
2 |
|
net-profit condition |
2 |
|
non-gaussian qmle |
2 |
|
panel data |
2 |
|
panel unit root test |
2 |
|
parameter estimation |
2 |
|
pearsonian qmle |
2 |
|
pearson’s type iv distribution |
2 |
|
poisson |
2 |
|
portmanteau test |
2 |
|
pre-averaging |
2 |
|
quasilikelihood ratio test |
2 |
|
random matrix theory |
2 |
|
randomized dividends |
2 |
|
realized covariance matrices |
2 |
|
realized kurtosis |
2 |
|
realized variance |
2 |
|
realized volatility |
2 |
|
relative value trading |
2 |
|
residual autocorrelations |
2 |
|
residual empirical process |
2 |
|
robustness |
2 |
|
ruin probability |
2 |
|
scenario test |
2 |
|
seemingly unrelated regression |
2 |
|
self-excited threshold process |
2 |
|
skewness |
2 |
|
spectral test |
2 |
|
spiked covariance matrix |
2 |
|
squared residual autocorrelation |
2 |
|
stationarity |
2 |
|
statistical arbitrage |
2 |
|
statistical inference |
2 |
|
stochastic difference equation |
2 |
|
stochastic return on investments |
2 |
|
stock indexes |
2 |
|
strong law of large numbers |
2 |
|
sure screening property |
2 |
|
tail behaviour |
2 |
|
tgarch-gc model |
2 |
|
threshold |
2 |
|
threshold garch model |
2 |
|
threshold ma-garch model |
2 |
|
threshold models |
2 |
|
time of ruin |
2 |
|
time series |
2 |
|
time series of counts |
2 |
|
trading volume |
2 |
|
value-at-risk |
2 |
|
vector autoregressive moving average |
2 |
|
volatility clustering |
2 |
|
water pollution - prevention and control |
2 |
|
weak arma models |
2 |
|
weibull distribution |
2 |
|
wild bootstrap |
2 |
|
wishart distribution |
2 |
|
zero-inflation |
2 |
|
additive outlier |
1 |
|
aic principle |
1 |
|
alpha-mixing |
1 |
|
arch |
1 |
|
arch model |
1 |
|
arch models |
1 |
|
arima and arch models |
1 |
|
arma time series |
1 |
|
attractor |
1 |
|
autocorrelation |
1 |
|
autocorrelations |
1 |
|
autopersistence function |
1 |
|
autopersistence graph |
1 |
|
autoregressive |
1 |
|
autoregressive conditional heteroscedasticity |
1 |
|
autoregressive conditional intensity |
1 |
|
autoregressive model |
1 |
|
autoregressive moving-average process |
1 |
|
autoregressive process |
1 |
|
autoregressive random variance process |
1 |
|
autoregressive transformation |
1 |
|
average derivative estimation |
1 |
|
bayes estimates |
1 |
|
bayes factor |
1 |
|
bayesian inference |
1 |
|
bias correction |
1 |
|
bic |
1 |
|
bilinear time series |
1 |
|
binary time series |
1 |
|
bivariate brownian motion |
1 |
|
box–jenkins approach |
1 |
|
break-point |
1 |
|
broken trend |
1 |
|
broken trend stationarity |
1 |
|
brownian motion |
1 |
|
business and economics |
1 |
|
callbacks |
1 |
|
causality in volatility |
1 |
|
chao phraya river |
1 |
|
chaos |
1 |
|
chaotic time series |
1 |
|
checking model adequacy |
1 |
|
chi-bar-square distributions |
1 |
|
classification |
1 |
|
complexity |
1 |
|
conditional heteroscedastic arma model |
1 |
|
conditional variance |
1 |
|
consistency |
1 |
|
corrected akaike information criterion |
1 |
|
correlation integral |
1 |
|
cramér-von mises test |
1 |
|
cross-correlation function |
1 |
|
cross-correlation tests |
1 |
|
cross-validation |
1 |
|
daily rainfall |
1 |
|
data augmentation |
1 |
|
data reconstruction |
1 |
|
diagnostic test |
1 |
|
diagonal |
1 |
|
dimension reduction |
1 |
|
discrete wavelet transformation |
1 |
|
dispersion model |
1 |
|
double sampling |
1 |
|
double-threshold autoregression |
1 |
|
dynamical systems |
1 |
|
economic systems and theories, economic history |
1 |
|
empirical bayes estimates |
1 |
|
estimating subgroup means |
1 |
|
evolutionary algorithms |
1 |
|
exceedances |
1 |
|
expectation-maximization algorithm |
1 |
|
exponential threshold model |
1 |
|
extreme value index |
1 |
|
false nearest neighbours |
1 |
|
far model |
1 |
|
forecasting |
1 |
|
fractional differencing |
1 |
|
fukushima nuclear disaster |
1 |
|
full rank maximum likelihood estimator |
1 |
|
full-rank and reduced-rank maximum likelihood estimators |
1 |
|
gamma mixture |
1 |
|
garch models |
1 |
|
gaussian measures |
1 |
|
generalized |
1 |
|
generalized degree of freedom |
1 |
|
generalized degrees of freedom |
1 |
|
generalized extreme value distribution |
1 |
|
generalized linear model |
1 |
|
generalized linear models |
1 |
|
generalized pareto distribution |
1 |
|
gibbs sampling |
1 |
|
goodness of fit |
1 |
|
goodness-of-fit |
1 |
|
hadamard product |
1 |
|
heteroscedastic |
1 |
|
hidden variables |
1 |
|
horvitz-thompson estimator |
1 |
|
hydrologic systems |
1 |
|
hydrological time series |
1 |
|
imputation |
1 |
|
independent realization |
1 |
|
index series |
1 |
|
infill asymptotics |
1 |
|
iteratively weighted least squares |
1 |
|
kalman filter |
1 |
|
kernel estimates |
1 |
|
kernel smoothing |
1 |
|
kullback-leibler information |
1 |
|
l-spline |
1 |
|
lagrange-multiplier test |
1 |
|
least squares estimator |
1 |
|
likelihood ratio |
1 |
|
limiting distribution |
1 |
|
local likelihood |
1 |
|
local linear smoother |
1 |
|
local models |
1 |
|
local polynomial fitting |
1 |
|
long memory models |
1 |
|
long-memory time series |
1 |
|
markov chain |
1 |
|
markov chain monte carlo |
1 |
|
markov regression model |
1 |
|
mathematics |
1 |
|
maximum likelihood |
1 |
|
maximum likelihood estimation |
1 |
|
maximum likelihood estimator |
1 |
|
maximum product of spacings |
1 |
|
mekong river |
1 |
|
micro-ergodic parameters |
1 |
|
misclassification |
1 |
|
mixture |
1 |
|
mixture autoregressive model |
1 |
|
mixture vector autoregressive model |
1 |
|
model |
1 |
|
model adequacy |
1 |
|
model checking |
1 |
|
model identification |
1 |
|
model selection |
1 |
|
monitoring datasets |
1 |
|
monotonic function estimation |
1 |
|
monte carlo markov chain |
1 |
|
moran's statistic |
1 |
|
multiple time series |
1 |
|
multivariate arch errors |
1 |
|
multivariate arch model |
1 |
|
multivariate arch process |
1 |
|
multivariate autoregressive conditional heteroscedasticity |
1 |
|
multivariate portmanteau statistic |
1 |
|
multivariate processes |
1 |
|
multivariate residual autocorrelation |
1 |
|
multivariate time series |
1 |
|
multivaritae time series |
1 |
|
negative-definite |
1 |
|
neighbourhood selection |
1 |
|
neural networks |
1 |
|
noise level |
1 |
|
non-gaussian innovations |
1 |
|
non-linear time series |
1 |
|
non-linear time series analysis |
1 |
|
non-linearity |
1 |
|
nonconstant correlation |
1 |
|
nonlinear models |
1 |
|
nonlinear time series models |
1 |
|
nonparametric autoregression |
1 |
|
nonparametric regression |
1 |
|
nonparametric time series |
1 |
|
observed information matrix |
1 |
|
order determination |
1 |
|
order selection |
1 |
|
overdispersion |
1 |
|
ozone |
1 |
|
parsimony |
1 |
|
partially linear model |
1 |
|
partially nonstationary |
1 |
|
peaks-over-threshold |
1 |
|
pearson residual |
1 |
|
phase space |
1 |
|
phase space reconstruction |
1 |
|
phase-space |
1 |
|
physics |
1 |
|
portmanteau statistic |
1 |
|
portmanteau tests: stationarity and ergodicity |
1 |
|
posterior odds ratio |
1 |
|
prediction |
1 |
|
predictive distributions |
1 |
|
principal hessian direction |
1 |
|
projection pursuit |
1 |
|
pseudo-likelihood function |
1 |
|
radial basis function network |
1 |
|
radial basis functions |
1 |
|
random coefficient model |
1 |
|
random coefficients |
1 |
|
randomized seasonal unit root |
1 |
|
randomized unit root |
1 |
|
reduced rank mle |
1 |
|
regression diagnostic |
1 |
|
regular and seasonal differencing |
1 |
|
regular and seasonal unit roots |
1 |
|
residual autocovariance |
1 |
|
residual autocovariance estimator |
1 |
|
response model |
1 |
|
robust estimation |
1 |
|
s-index |
1 |
|
score statistic |
1 |
|
score test |
1 |
|
score-based test |
1 |
|
semiparametrics |
1 |
|
single-index coefficient models |
1 |
|
single-index model |
1 |
|
space-time data |
1 |
|
squared residuals |
1 |
|
standard errors |
1 |
|
star product |
1 |
|
state space model |
1 |
|
stochastic integral |
1 |
|
stochastic trend |
1 |
|
stochastic volatility |
1 |
|
strongly mixing |
1 |
|
strongly mixing sequence |
1 |
|
structural change |
1 |
|
subset model |
1 |
|
sum of squared residual autocorrelations |
1 |
|
super-consistency |
1 |
|
superdiagonal and sub-diagonal models |
1 |
|
superpopulation model |
1 |
|
testing for statistical independence |
1 |
|
threshold autoregressive (tar) time series models |
1 |
|
threshold time series model |
1 |
|
unit root |
1 |
|
unit root test |
1 |
|
unstable arma models |
1 |
|
valid covariance models |
1 |
|
varying-coefficient model |
1 |
|
vector ar-garch model |
1 |
|
wiener process |
1 |
|
ρ-mixing |
1 |
