Integer-Valued Split-BREAK Process with a General Family of Innovations and Application to Accident Count Data Modeling
Axioms,
Journal Year:
2024,
Volume and Issue:
13(1), P. 40 - 40
Published: Jan. 7, 2024
This
paper
presents
a
novel
count
time-series
model,
named
integer-valued
Split-BREAK
process
of
the
first
order,
abbr.
INSB(1)
model.
is
examined
in
terms
its
basic
stochastic
properties,
such
as
stationarity,
mean,
variance
and
correlation
structure.
In
addition,
marginal
distribution,
over-dispersion
zero-inflation
properties
are
also
examined.
To
estimate
unknown
parameters
process,
an
estimation
procedure
based
on
probability
generating
functions
(PGFs)
proposed.
For
obtained
estimators,
their
asymptotic
well
appropriate
simulation
study,
Finally,
applied
dynamic
analysis
some
real-world
series,
namely,
numbers
serious
traffic
accidents
Serbia
forest
fires
Greece.
Language: Английский
Poisson-Lindley minification INAR process with application to financial data
AIMS Mathematics,
Journal Year:
2024,
Volume and Issue:
9(8), P. 22627 - 22654
Published: Jan. 1, 2024
<p>This
paper
introduces
the
Poisson-Lindley
minification
integer-valued
autoregressive
(PL-MINAR)
process,
a
novel
statistical
model
for
analyzing
count
time
series
data.
The
modified
negative
binomial
thinning
and
(PL)
marginal
distribution
served
as
foundation
model.
proposed
was
examined
in
terms
of
its
basic
stochastic
properties,
especially
related
to
conditional
measures
(e.g.,
transition
probabilities,
mean
variance,
autocorrelation
function).
Through
comprehensive
simulations,
effectiveness
various
parameter
estimation
techniques
validated.
PL-MINAR
model's
practical
utility
demonstrated
number
Bitcoin
transactions
stock
trades,
showing
superior
or
comparable
performance
established
INAR
By
offering
robust
tool
financial
analysis,
this
research
holds
potential
significant
improvements
forecasting
understanding
market
dynamics.</p>
Language: Английский
INAR(1) process with weighted negative binomial Lindley distributed innovations and applications to criminal and COVID-19 data
Communications in Statistics - Simulation and Computation,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 18
Published: April 15, 2024
In
this
study,
we
introduce
a
pliant
stationary
first-order
integer-valued
autoregressive
(INAR)
process
with
weighted
negative
binomial
Lindley
innovations.
The
main
properties
of
the
model
are
derived.
methods
conditional
maximum
likelihood,
least
square
and
Yule-Walker
used
for
estimating
parameters,
while
efficiency
these
three
is
evaluated
through
simulation
study.
Finally,
practical
aspect
proposed
INAR(1)
discussed
on
two
time
series
monthly
number
criminal
mischief
reports
in
Pittsburgh
daily
COVID-19
death
cases
Paraguay.
Language: Английский