Ismail Shah

Quaid-i-Azam University | QAU · Department of Statistics

This work proposes a new approach for the prediction of the electricity price based on forecasting aggregated demand and supply curves. The basic idea is to model the hourly demand and the supply curves, to predict them and to find the intersection of the predicted curves in order to obtain the predicted equilibrium market price and volume. Modelin...

Efficient modeling and forecasting of electricity demand and prices is an important issue in competitive electricity markets. This work investigates the forecasting performance of several models for the one-day-ahead prediction of demand and prices on four electricity markets (APX Power-UK, Nord Pool, PJM and IPEX). All the models are based on two...

Ridge regression is used to circumvent the problem of multicollinearity among predictors and many estimators for ridge parameter k are available in the literature. However, if the level of collinearity among predictors is high, the existing estimators also have high mean square errors (MSE). In this paper, we consider some existing and propose new...

Currently, in most countries, the electricity sector is liberalized, and electricity is traded in deregulated electricity markets. In these markets, electricity demand is determined the day before the physical delivery through (semi-)hourly concurrent auctions. Hence, accurate forecasts are essential for efficient and effective management of power...

Efficient modeling and forecasting of electricity prices are essential in today’s competitive electricity markets. However, price forecasting is not easy due to the specific features of the electricity price series. This study examines the performance of an ensemble-based technique for forecasting short-term electricity spot prices in the Italian e...

Regularization regression techniques are widely used to overcome a model's parameter estimation problem in the presence of multicollinearity. Several biased techniques are available in the literature, including ridge, Least Angle Shrinkage Selection Operator (LASSO), and elastic net. In this work, we study the performance of the classical LASSO, ad...

Several control charts have been developed in the literature to monitor zero inflation using classic and simple linear regression models with covariates. Simple linear regression models may not be appropriate, especially when the response variable is skewed or count. When the response distribution follows the exponential family; however, the genera...

In recent decades, the primary intention of neuroscientists and psychiatrists been to evaluate the connectivity between brain regions and psychiatric disorders. The amygdala has central immersion in memory alliance, stress response, emotional perception, and automatic responses to emotional stimuli. This paper uses a meta-analysis approach to estab...

Citation: Shah, I, Ejaz, Z, Ali, S (2022): Modeling the Determinants of Out of School Children in Pakistan ------------------------------------------ ------------------------------------------ Abstract: It is well known that different socioeconomic, household sizes, school levels, and cultural factors are highly related to the problem of out of sch...

Nowadays, short-term traffic flow forecasting has gained increasing attention from researchers due to traffic congestion in many large and medium-sized cities that pose a serious threat to sustainable urban development. To this end, this research examines the forecasting performance of functional time series modeling to forecast traffic flow in the...

The recent industrial revolution is a result of modern technological advancement and industrial improvements require quick detection of assignable causes in a process. Tis study presents a monitoring scheme for unit interval data assuming beta and unit Nadarajah and Haghighi distributions. To this end, a maximum exponentially weighted moving averag...

To monitor time and magnitude, different types of control charts have been proposed in the literature. This article proposes a new maximum exponentially weighted moving average (Max-EWMA) control chart by assuming Weibull distribution. The test-statistic of the Max-EWMA chart consists of two EWMA statistics, where one statistic is used for monitori...

The receiver operating characteristics (ROC) analysis is commonly used in clinical settings to check the performance of a single threshold for distinguishing population-wise bimodal-distributed test results. However, for population-wise three-modal distributed test results, a single threshold ROC (stROC) analysis showed poor discriminative performa...

In additive manufacturing, geometric shape deviations are built through statistical deviation models. Nonetheless, the resource constraints limit the manufacturers to test shapes. However, in addition to the power, the simplicity of the deviation models has been demonstrated with illustrative cases for in-plane deviation modelling for regular penta...

Control charts are used to detect assignable causes in different manufacturing and nonmanufacturing processes. is study presents a new maximum exponentially weighted moving average (Max-EWMA) chart for joint unit interval time and magnitude monitoring. To this end, beta distribution is considered for time whereas simplex distribution is used for ma...

Electricity demand and price forecasting are key components for the market participants and system operators as precise forecasts are necessary to manage power systems effectively. However, forecasting electricity demand and prices are challenging due to their specific features, such as high frequency, volatility, long trend, nonconstant mean and v...

Pakistan is currently facing the fourth wave of the deadly coronavirus, which was first reported in Wuhan, China, in December 2019. This work utilizes the epidemiological models to analyze Pakistan’s COVID-19 data. The basic susceptible, infected, and recovered (SIR) model is studied assuming Bayesian and time-series SIR (tSIR) approaches. Many stu...

In today's liberalized electricity markets, modeling and forecasting electricity demand data are highly important for the effective management of the power system. However, electricity demand forecasting is a challenging task due to the specific features it exhibits. These features include the presence of extreme values, spikes or jumps, multiple p...

In the manufacturing industry, process surveillance plays an important role in improving product reliability. Many monitoring procedures have been devised to improve the reliability of a product in the literature. Due to cascading nature of multistage processes, the quality variable of the final stage can be influenced by the quality variable in th...

In recent years, efficient modeling and forecasting of electricity prices became highly important for all the market participants for developing bidding strategies and making investment decisions. However, as electricity prices exhibit specific features, such as periods of high volatility, seasonal patterns, calendar effects, nonlinearity, etc., th...

The convolution of the independent Gaussian and exponential distribution is known as the exponentially modified Gaussian (EMG) distribution. The main feature of this distribution is its differential behavior on the right and left tails. The distribution exhibits a normally distributed left tail and an exponentially-distributed right tail. This dist...

Joint monitoring of time and magnitude is an important issue in many industrial and non-industrial fields and several proposals exist in the literature. The aim of this article is to propose a new maximum exponentially weighted moving average (Max-EWMA) chart assuming generalized exponential distribution for time as well as magnitude. As the test-s...

Quick detection of an assignable cause is necessary for process accuracy with respect to the specifications. The aim of this study is to monitor the time and magnitude processes based on unit-interval data. To this end, maximum exponentially weighted moving average (Max-EWMA) control chart for simultaneous monitoring time and magnitude of an event...

This article assesses the robustness of shape parameter for Bayesian acceptance sampling plans assuming Erlang and Weibull distributions. In particular, the prior information on the parameter is combined assuming different loss functions to derive different sampling plans. The cost model for the group sampling plans is studied by satisfying the con...

The present communication develops the tools for Bayesian prediction of the Gompertz distribution based on CSPALT. The Metropolis-Hastings algorithm is applied to evaluate the BPIs for a censored sample based on unified hybrid censoring scheme. In order to investigate the impact of methodologies adopted, two numerical examples are performed. The si...

Monitoring time and magnitude jointly is an attractive field due to their vast applications in different industries. This article presents a new maximum exponentially weighted moving average (Max-EWMA) chart assuming exponentially modified Gaussian (EMG) distribution for time and magnitude. The reason of considering Max-EWMA chart is its flexibilit...

In practice, the data related to rates and proportion may have excess of ones wherein the beta distribution does not fit well. To deal with the inflation of ones, this article introduces unit Nadarajah and Haghighi distribution. Besides deriving statistical properties of the proposed distribution, several estimation methods are discussed. In partic...

Monitoring censored data is a challenging task as the traditional charts reported poor performance in the case of censored data. This article presents exponentially weighted moving average control charts for monitoring type-I censored data assuming generalized exponential (GE) distribution. In particular, we replace the censored observation with th...

This article presents deviation based exponentially weighted moving average control charts to monitor type-I censored data. Due to practical applications, this study considers Weibull distribution to assess the performance of the proposed memory-type control charts. The censored observations are replaced with the conditional expected value (CEV), c...

Nowadays, modeling and forecasting electricity spot prices are challenging due to their specific features, including multiple seasonalities, calendar effects, and extreme values (also known as jumps, spikes, or outliers). This study aims to provide a comprehensive analysis of electricity price forecasting by comparing several outlier filtering tech...

Different probability models are used to model survival data. However, it is important to know which model describe best the data because if the assumptions for parametric methods hold, the resulting estimates have smaller standard errors and are easier to interpret and helps in predictions. This article presents the Bayesian censored data modeling...

Monitoring censored data is a challenging task and for this purpose, many control charts have been proposed in the literature using different methodologies. In particular, conditional expected value (CEV) and conditional median (CM) are commonly used to replace the censored observations for efficient monitoring. These central tendency measures do n...

Reliability of products is a key factor for successful businesses. In general, the existing monitoring schemes have poor performance as reliability data are often censored. Also, the products are manufactured in multistage processes where the outgoing quality gets affected by the previous stage quality. Besides this cascade property, historical dat...

Regression techniques are generally used to predict a response variable using one or more predictor variables. In many fields of study, the regressors can be highly intercorrelated, which leads to the problem of multicollinearity. Consequently, the ordinary least squares estimates become inconsistent and lead to wrong inferences. To handle the prob...

Early detection of a disease risk plays a vital role in successful treatment of the disease. Many chronic diseases, e.g., stroke, can be treated satisfactorily if they can be detected early. Traditionally, people evaluate their health conditions by comparing the current readings of their medical risk factors with some threshold values, and if irreg...

This study aims to detect the most recent changepoint in censored panel data by ignoring dependence within and between segments as well as taking into account the serial autocorrelation. A comparison of different methods to detect the most recent changepoint for censored data is presented. Different censoring rates such as 20%, 50%, and 90% in the...

An extension of the exponential distribution due toNadarajah and Haghighi referred to as Nadarajah and Haghighi (NH) distribution is an alternative that always provides better fits than the gamma, Weibull, and the generalized exponential distributions whenever the data contains zero values. However, in practice, discrete data is easy to collect as...

This article deals with the monitoring of censored data using the cumulative sum (CUSUM) control charts for Weibull lifetimes under type-I censoring. To develop an efficient CUSUM structure for censored data, we use the conditional expected value (CEV) and conditional median (CM) approaches. In particular , we focus on the detection of shifts in th...

In the modern industrial age, regular system maintenance is an integral process because systems, both engineering and nonengineering, deteriorate over time. Statistical process monitoring techniques, especially control charts, are very helpful in monitoring the performance of such systems and consequently help in decision making on whether maintena...

Over the last three decades, accurate modeling and forecasting of electricity prices has become a key issue in competitive electricity markets. As electricity price series usually exhibit several complex features, such as high volatility, seasonality, calendar effect, non-stationarity, non-linearity and mean reversion, price forecasting is not a tr...

To study the high quality processes, time-between-events (TBE) control charts have several advantages over the ordinary control charts. However, the existing TBE charts are based on the exponential distribution, which limit the application of these charts to monitor rare events. Therefore, to generalize existing exponential TBE charts, recently two...

A control chart named as the hybrid double exponentially weighted moving average (HDEWMA) to monitor the mean of Weibull distribution in the presence of type-I censored data is proposed in this study. In particular, the focus of this study is to use the conditional median (CM) for the imputation of censored observations. The control chart performan...

Electronic devices are integral part of our life and modeling their lifetime is the most challenging and interesting field in reliability analysis. To investigate the failure behavior of electronic devices reliability analysis is commonly used. In the literature, however, it is reported that one in five electronic device failure is a result of corr...

The increasing shortage of electricity in Pakistan disturbs almost all sectors of its economy. As, for accurate policy formulation, precise and efficient forecasts of electricity consumption are vital, this paper implements a forecasting procedure based on components estimation technique to forecast medium-term electricity consumption. To this end,...

Control charts are a popular statistical process control (SPC) technique for monitoring to detect the unusual variations in different processes. Contrary to the classical charts, control charts have also been modified to include covariates using regression approaches. This study assesses the performance of risk-adjusted control charts under the com...

Time Between Events (TBE) charts have advantages over the traditional control charts when monitoring high quality processes with very low defect rates. This article introduces a new discrete TBE control chart following discrete Weibull distribution. The design of the proposed chart is derived analytically and discussed numerically. Moreover, the pe...

This article presents the Bayesian and classical inferences for the Chen distribution assuming upper record values. As the posterior distribution is not in a closed form, a Markov Chain Monte Carlo method is presented to obtain the posterior summaries. To assess the effect of prior on the estimated parameters, sensitivity analysis is also a part of...

Transmuted distributions are flexible skewed families constructed by the induction of one or more additional parameters to a parent distribution. This paper investigates the potential usefulness of a two-component mixture of Transmuted Pareto Distribution (TPaD) under a Bayesian framework assuming type-I right censored sampling. For Bayesian analys...

Control charts are efficient process monitoring tools used to distinguish between assignable and natural variations. This article presents a new time-between-events chart to monitor the scheduled time. In particular, exponentially modified Gaussian distribution is considered in the construction of the control chart. The performance of the chart is...

The exponential distribution is commonly used to model different phenomena in statistics and reliability engineering. A new extension of exponential distribution known as the Nadarajah and Haghighi [An extension of the exponential distribution, Statistics: A Journal of Theoretical and Applied Statistics, 2011,45, 543-558.] distribution was introduc...

To detect the changepoint, this package uses most recent changepoint, double cumulative sum binary segmentation, multiple changepoints in multivariate time series, analyzing each series in the panel independently, and analyzing aggregated data methods. This package is useful to simulate censored time series to detect the most recent changepoint in...

This study deals with the reliability analysis of electronic devices under different voltages assuming modified beta generalized Weibull distribution using power law rule. The parameters of the modified distribution are estimated using Bayesian inference as it allows to incorporate the prior information. Sensitivity of hyperparameters and selection...

In deregulated electricity markets, accurate modeling and forecasting of different variables, e.g. demand, prices, production etc. have obtained increasing importance in recent years. As in most electricity markets, the daily demand and prices are determined the day before the physical delivery by means of (semi-) hourly concurrent auctions, accura...

Efficient modeling and forecasting for the electricity demand is an important issue in competitive electricity market. In most electricity markets the daily demand is determined the day before the delivery by means of (semi-)hourly auctions for the following day. Therefore, adequate and reliable day-ahead demand forecasts are very important. In thi...

In analyzing demographic data it is important to flexibly model the relation between a variable of interest and a set of covariates. Most of the literature traditionally focuses on generalized linear models or generalized linear mixed models, with normally distributed random effects accounting for the hierarchical data structure. Inappropriately as...