scholarly journals Outlier Detection in Local Level Model: Impulse Indicator Saturation Approach

2019 ◽  
Vol 7 (4A) ◽  
pp. 41-48
Author(s):  
F. Z. Che Rose ◽  
M. T. Ismail ◽  
N. A. K. Rosili
Keyword(s):  
Outlier Detection ◽  
Local Level ◽  
Level Model ◽  
Impulse Indicator Saturation

scholarly journals Outliers detection in state-space model using indicator saturation approach

2021 ◽  
Vol 22 (3) ◽  
pp. 1688
Author(s):  
Farid Zamani Che Rose ◽  
Mohd Tahir Ismail ◽  
Mohd Hanafi Tumin
Keyword(s):  
Structural Changes ◽  
Stock Exchange ◽  
Local Level ◽  
State Space Model ◽  
Model Framework ◽  
Suggested Approach ◽  
Level Model ◽  
The Mean ◽  
Impulse Indicator Saturation ◽  
Detection Of Outliers

Structural changes that occur due to outliers may reduce the accuracy of an estimated time series model, shifting the mean distribution and causing forecast failure. This study used general-to-specific approach to detect outliers via indicator saturation approach in the local level model framework. Focusing on impulse indicator saturation, performance recorded by the suggested approach was evaluated using Monte Carlo simulations. To tackle the issue of higher number of regressors compared to the number of observations, this research utilized the split-half approach algorithm. We found that the impulse indicator saturation performance relies heavily on the size of outlier, location of outlier and number of splits in the series examined. Detection of outliers using sequential and non-sequential algorithms is the most crucial issue in this study. The sequential searching algorithm was able to outperform the non-sequential searching algorithm in eliminating the non-significant indicators based on potency and gauge. The outliers captured using impulse indicator saturation in financial times stock exchange (FTSE) United States of America (USA) shariah index correspond to the financial crisis in 2008-2009.

A comparison of methods for bootstrapping in the local level model

2001 ◽  
Vol 21 (1) ◽  
pp. 27-38 ◽  
Author(s):  
Glaura C. Franco ◽  
Reinaldo C. Souza
Keyword(s):  
Local Level ◽  
Comparison Of Methods ◽  
Level Model

scholarly journals METODE STATE SPACE DALAM MERAMALKAN JUMLAH PENUMPANG KERETA API DI PULAU JAWA

2020 ◽  
Vol 9 (1) ◽  
pp. 8
Author(s):  
FITRI ANANDA DITA SARASWITA ◽  
I WAYAN SUMARJAYA ◽  
LUH PUTU IDA HARINI
Keyword(s):  
State Space ◽  
Time Series Data ◽  
Local Level ◽  
State Space Model ◽  
The State ◽  
Series Data ◽  
State Space Method ◽  
Dynamic Interactions ◽  
Level Model ◽  
Space Method

State space is an approach to model and predict together several time series data that are interconnected, and these variables have dynamic interactions. The purpose of this research is to model the number of train passengers in Java and find out the forecasting results using the state space method. The algorithm used to solve the state space model is the Kalman filter. In this research, a suitable final model is local level model with seasonal and produces MAPE value of 2%, this shows that the state space method is very accurately.

Tolerance-Maps Applied to a Point-Line Cluster of Features

2005 ◽  
Author(s):  
Gaurav Ameta ◽  
Joseph K. Davidson ◽  
Jami J. Shah
Keyword(s):  
Dimensional Space ◽  
Local Level ◽  
Relative Location ◽  
Global Level ◽  
Tolerance Zone ◽  
Geometric Tolerances ◽  
Level Model ◽  
Cluster A ◽  
Point Line ◽  
Picture Frame

In this paper, groups of individual features, i.e. a point, a line, and a plane, are called clusters and are used to constrain sufficiently the relative location of adjacent parts. A new mathematical model for representing geometric tolerances is applied to a point-line cluster of features that is used to align adjacent parts in two-dimensional space. First, tolerance-zones are described for the point-line cluster. Then, a Tolerance-Map®, a hypothetical volume of points, is established which is the range of a mapping from all possible locations for the features in the cluster. A picture frame assembly of four parts is used to illustrate the accumulations of manufacturing variations, and the T-Maps provide stackup relations that can be used to allocate size and orientational tolerances. This model is one part of a bi-level model that we are developing for geometric tolerances. At the local level the model deals with the permitted variations in a tolerance zone, while at the global level it interrelates all the frames of reference on a part or assembly.

scholarly journals Distribution of the ML Estimator of an MA(1) and a local level model

1993 ◽  
Vol 9 (3) ◽  
pp. 377-401 ◽  
Author(s):  
Neil Shephard
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimator ◽  
Related Problem ◽  
Moving Average ◽  
Local Level ◽  
Likelihood Estimator ◽  
Moving Average Models ◽  
Level Model ◽  
Ml Estimator ◽  
Made In

Although considerable attention has recently been paid to the behavior of the maximum likelihood estimator of simple moving average models, little progress has been made in finding a good approximation to its distribution in cases where the process is close to being noninvertible. In this paper a method is produced that gives an excellent approximation to the distribution function, even in the case where the process is strictly noninvertible. Also studied is the related problem of the distribution of the maximum likelihood estimator of the signalto-noise ratio in the local level model.

Do You Want to See the Tree? Ignore the Forest

2014 ◽  
Vol 61 (3) ◽  
pp. 205-214 ◽  
Author(s):  
Nicolas Poirel ◽  
Claire Sara Krakowski ◽  
Sabrina Sayah ◽  
Arlette Pineau ◽  
Olivier Houdé ◽  
...  
Keyword(s):  
Visual Recognition ◽  
Local Level ◽  
Local Information ◽  
Visual Environment ◽  
Global Information ◽  
Focus Attention ◽  
Global Level ◽  
Hierarchical Stimuli ◽  
Priming Paradigm ◽  
The One

The visual environment consists of global structures (e.g., a forest) made up of local parts (e.g., trees). When compound stimuli are presented (e.g., large global letters composed of arrangements of small local letters), the global unattended information slows responses to local targets. Using a negative priming paradigm, we investigated whether inhibition is required to process hierarchical stimuli when information at the local level is in conflict with the one at the global level. The results show that when local and global information is in conflict, global information must be inhibited to process local information, but that the reverse is not true. This finding has potential direct implications for brain models of visual recognition, by suggesting that when local information is conflicting with global information, inhibitory control reduces feedback activity from global information (e.g., inhibits the forest) which allows the visual system to process local information (e.g., to focus attention on a particular tree).

Sign in / Sign up

Export Citation Format

Share Document