Academic literature on the topic 'Error component random parameter logit model'

Until now, no research has been carried out in Croatia into consumer preferences for a particular agricultural and food product by a choice experiment. Therefore, little data are available about Croatian consumers' preferences for social concerns (sustainability, biodiversity, rural development and animal welfare) with regard to the consumer choice and behavior favoring local pig breeds, in this case the Black Slavonian Pig breed. A survey was the method used to collect the data, and a survey questionnaire was used as an instrument. The survey was performed on a sample of n = 100 Croatian consumers surveyed online using a hypothetical choice experiment. The data were analyzed using the three logit models: a multinomial logit model (MNL), random parameter logit (RPL), and an error component random parameter logit model (RPL-EC) in order to examine the consumers’ heterogeneous preferences for fresh ham meat of the Black Slavonian Pig. The results suggest that the Croatian consumers appreciated a darker red fresh pork meat than the one obtained from the Black Slavonian Pig reared outdoors and semi-outdoor. They also prefer a fresh meat bearing a geographical information label, such as the continental Croatia and continental Croatia + PDO, to a fresh meat without a label.

Life course events can change household travel demand dramatically. Recent studies of car ownership have examined the impacts of life course events on the purchasing, replacing, and disposing of cars. However, with the increasing diversification of mobility tools, changing the fleet size is not the only option to adapt to the change caused by life course events. People have various options with the development of sustainable mobility tools including electric car, electric bike, and car sharing. In order to determine the impacts of life course events on car ownership and the decision of mobility tool type, a stated choice experiment was conducted. The experiment also investigated how the attributes of mobility tools related to the acceptance of them. Based on existing literature, we identified the attributes of mobility tools and several life course events which are considered to be influential in car ownership decision and new types of mobility tools choice. The error component random parameter logit model was estimated. The heterogeneity across people on current car and specific mobility tools are considered. The results indicate people incline not to sell their current car when they choose an electric bike or shared car. Regarding the life course events, baby birth increases the probability to purchase an additional car, while it decreases the probability to purchase an electric bike or joining a car sharing scheme. Moreover, the estimation of error components implies that there is unobserved heterogeneity across respondents on the sustainable mobility tools choice and the decision on household’s current car.

Zero-inflated regression models have had wide application recently and have provenuseful in modeling data with many zeros. Zero-inflated Binomial (ZIB) regression model is an extension of the ordinary binomial distribution that takes into account the excess of zeros. In comparing the probit model to the logistic model, many authors believe that there is little theoretical justification in choosing one formulation over the other in most circumstances involving binary responses. The logit model is considered to be computationally simpler but it is based on a more restrictive assumption of error independence, although many other generalizations have dealt with that assumption as well. By contrast, the probit model assumes that random errors have a multivariate normal distribution. This assumption makes the probit model attractive because the normal distribution provides a good approximation to many other distributions. In this paper, we develop a maximum likelihood estimation procedure for the parameters of a zero-inflated Binomial regression model with probit link function for both component of the model. We establish the existency, consistency and asymptotic normality of the proposed estimator.

This research explored the commuting mode preferences of students living near Institut Teknologi Bandung when a new mode of transportation (i.e., carpool) is introduced to the selection list. Six alternative modes were presented: minibus, car, motorcycle, car-based ride-sourcing, motorcycle-based ride-sourcing, and carpool. The data collection process was conducted using a questionnaire-based stated-preferences survey. It included eight sets of labeled scenarios with a number of attributes: travel time, travel cost, waiting time, transfer amount, access and egress time, frequency, congestion time, baggage cost, and parking cost. A total of 1416 observations were acquired for further analysis. A mixed logit (MXL) model with random cost parameter and random error components was used. From the MXL results, we found that travel cost had no significant influence on the selection of commuting mode among students. This result was unforeseen given the characteristics of Indonesian consumers, who are notoriously sensitive to price. However, based on the results for several significant attributes of carpool as well as from the value of travel time savings and demand calculation, we suggest that carpooling is a valid alternative transport mode for campus commuting. As a pioneer study on student commuting mode selection, this study provided valid and dependable evidence on how students around ITB main campus choose their transportation methods. Abstrak. Penelitian ini mengeksplorasi preferensi moda perjalanan pulang pergi mahasiswa yang tinggal di dekat Institut Teknologi Bandung ketika moda transportasi baru (yaitu angkutan bersama) menjadi salah satu pilihan moda. Terdata enam moda alternatif yang disajikan: angkot, mobil, sepeda motor, taksi daring, ojek daring, dan angkutan bersama. Proses pengumpulan data dilakukan dengan menggunakan metoda survei stated-preference berbasis kuesioner. Survei tersebut meliputi delapan skenario berlabel dengan sejumlah atribut: waktu perjalanan, biaya perjalanan, waktu tunggu, banyaknya perpindahan moda, waktu perjalanan menuju tempat angkutan umum dan waktu perjalanan menuju tempat tujuan, frekuensi kedatangan, waktu kemacetan, biaya bagasi, dan biaya parkir. Sebanyak 1416 pengamatan diperoleh untuk analisis lebih lanjut. Model mixed logit (MXL) dengan parameter biaya acak dan komponen error acak digunakan. Dari hasil MXL, kami menemukan bahwa biaya perjalanan tidak berpengaruh signifikan terhadap pemilihan moda perjalanan pulang pergi di kalangan mahasiswa. Hasil ini tidak terduga mengingat karakteristik konsumen Indonesia yang terkenal sensitif terhadap harga. Namun, berdasarkan hasil untuk beberapa atribut signifikan dari angkutan bersama serta dari nilai penghematan waktu perjalanan dan perhitungan permintaan, kami menyarankan bahwa angkutan bersama adalah moda transportasi alternatif yang valid untuk komuter kampus. Sebagai studi perintis dalam pemilihan moda perjalanan pulang pergi mahasiswa, studi ini memberikan bukti yang valid dan dapat diandalkan tentang bagaimana mahasiswa di sekitar kampus utama ITB memilih metode transportasi mereka. Keywords. angkutan bersama, mahasiswa ITB, mixed logit, elastisitas, nilai waktu.

This article is concerned with the estimating problem of heteroscedastic partially linear errorsin- variables (EV) models. We derive the strong consistency rate for estimators of the slope parameter and the nonparametric component in the case of known error variance with negative association (NA) random errors. Meanwhile, when the error variance is unknown, the strong consistency rate for the estimators of the slope parameter and the nonparametric component as well as variance function are considered for NA samples. In general, we concluded that the strong consistency rate for all estimators can achieve o(n-1/4).

The relationship between the uncertainty (4π times the product of rms duration, Dt, and rms bandwidth, Df) and the variance of energy estimates of random transients is examined. If a transient can be modeled with the product model, it is shown that for many cases the normalized error in the energy estimate, as measured by the uncertainty, is approximately the same as the normalized error determined from the more exact statistical duration and bandwidth. The uncertainty is a quantitative measure of the expected energy estimate errors. If the transient has a significant random component, a small uncertainty parameter implies a large error in the energy estimate. Attempts to resolve a time/frequency spectrum near the uncertainty limits of a transient with a significant random component will result in large errors in the spectral estimates.

A product model, in which{x(t)}, is the product of a slowly varying random window,{w(t)}, and a stationary random process,{g(t)}, is defined. A single realization of the process will be defined asx(t). This is slightly different from the usual definition of the product model where the window is typically defined as deterministic. An estimate of the energy (the zero order temporal moment, only in special cases is this physical energy) of the random process,{x(t)}, is defined asm0=∫∞∞|x(t)|2dt=∫−∞∞|w(t)g(t)|2dtRelationships for the mean and variance of the energy estimates,m0, are then developed. It is shown that for many cases the uncertainty (4πtimes the product of rms duration,Dt, and rms bandwidth,Df) is approximately the inverse of the normalized variance of the energy. The uncertainty is a quantitative measure of the expected error in the energy estimate. If a transient has a significant random component, a small uncertainty parameter implies large error in the energy estimate. Attempts to resolve a time/frequency spectrum near the uncertainty limits of a transient with a significant random component will result in large errors in the spectral estimates.

The application of investment casting process is rapidly increasing, specifically for near net shape manufacturing of complex and small engineering components. The process begins with making of wax patterns, thereafter employing a precision mould, dewaxing, pouring molten alloy and knocking the shell, followed by minor finishing operations. This study is about predicting the quality of responses of the wax patterns namely linear shrinkage and surface roughness using fuzzy-based artificial neural network. The process parameters considered are injection temperature, injection pressure and holding time, and experiments have been performed as per Taguchi’s L18 orthogonal array. As optimum parameter levels were different for both the responses, fuzzy logic reasoning has been used to combine all the objectives and transform the experimental results into single performance index known as multi-response performance index. Later, modelling of the process has been done using artificial neural network with experimental process parameters as inputs and multi-response performance index as output obtained from fuzzy modelling. Further, experiments have been conducted at random combination of parameter levels to validate the developed model, and it has been found that the actual results agreed well with that of the predicted value on the basis of mean absolute percentage error and correlation plots.

Generalized linear models were used to investigate the sensitivity of paramater estimates to choice of the random error assumption in models of fisheries data. We examined models of fish yield from lakes as a function of (i) Ryder's morphoedaphic index, (ii) lake area, lake depth, and concentration of dissolved solids, and (iii) fishing effort. Models were fit using a normal, log-normal, gamma, or Poisson distribution to generate the random error. Plots of standardized Pearson residuals and standardized deviance residuals were used to evaluate the distributional assumptions. For each data set, observations were found to be consistent with several distributions; however, some distributions were shown to be clearly inappropriate. Inappropriate distributional assumptions produced substantially different parameter estimates. Generalized linear models allow a variety of distributional assumptions to be incorporated in a model, and thereby let us study their effects.

Abstract The predicting methodology the state of the object based on diagnostic data is considered. With the selected parameter that determines the state of the object, it is measured in real time at a fixed sampling step. According to the measurement data, the value of this parameter is predicted in the future. This operation is implemented by an extrapolator of the l order - a l degree polynomial, built using the least squares method based on the previous measurements results. The changing process model of the diagnosed parameter is a random time function described by the stationary centered random component sum and a mathematical expectation deterministic change. The estimating prediction error method and the extrapolator parameters influence on its value are presented.

Qualsiasi prodotto alimentare che si trova sul mercato contiene diverse etichette che aiutano i consumatori nel loro processo decisionale quando fanno acquisti. Questo aiuto può essere garantito solo se i consumatori comprendono il significato di queste etichette, le differenze tra loro e le informazioni che certificano. La tesi ha esplorato il ruolo delle etichette nel settore del marketing alimentare usando studi condotti sull'approccio del consumatore. Utilizzando diversi metodi (statistici ed econometrici), abbiamo analizzato le percezioni, la consapevolezza e la conoscenza dei consumatori verso alcune etichette alimentari e le loro preferenze e comportamenti verso i prodotti alimentari che portano queste etichette (etichette nutrizionali sul fronte della confezione e marchi di qualità europei). I prodotti alimentari certificati di qualità sono stati scelti perché sono drammaticamente rilevanti per il settore agroalimentare europeo, e ancora di più per quello italiano dove costituisce la DOP Economy, data la sua densità. Sulla base dei risultati abbiamo formulato alcune raccomandazioni di marketing, policy, e di comunicazione che potrebbero essere utilizzate dai consorzi per migliorare l'impegno dei consumatori per i prodotti con marchi di qualità. Le raccomandazioni sono state rivolte anche ai policy maker e ai produttori dei prodotti DOP/IGP/STG/Organici ma anche ai policy maker dell'Etichettatura Nutrizionale.
Any food product found on the market contains several labels that help consumers in their decision making when shopping. This help can be guaranteed only if the consumers understand the significance of those labels, the differences between them and the information that they certify. The thesis explored labels’ role in the food marketing sector and studies were carried out according to consumer approach. Using different methods (statistics and econometrics), we analyzed consumers perceptions, awareness, knowledge towards some food labels and their preferences and behavior toward food products bearing these labels (Front of Packaging Nutritional Labels and Quality labels). Quality certified food products were chosen because are dramatically relevant for the European agri-food sector, even more of the Italian one where it forms the DOP Economy, due to its density. Assessments of several food labels from a consumer behavior perspective was carried out. Based on the findings we formulated some policy, marketing recommendations and communication suggestions that could be used by the consortia to enhance consumers’ engagement for products with quality certifications (PDO/PG/TSG or organic). The recommendations were also addressed to policy makers and producers of the PDO/PGI/TSG/Organic products but also to the policy makers of the Nutritional Labelling.

The objective of this study is to evaluate the total least squares (TLS) estimator for the linear mixed model when the design matrix is subject to measurement errors, with special focus on models for longitudinal or repeated-measures data. We consider measurement errors only in the design matrix concerning the fixed part of the model and estimate its corresponding parameter vector under the TLS set up. After treating two variants of the general case, the random coefficient model is discussed as a special case. We evaluate conditions, on the design matrices as well as on variance component parameters, under which a reasonable TLS estimator can be expected in such models. Analysis of a real data example is also provided.

"The transmission system is subjected to multi-harmonic torque excitation of the engine, random excitation of road, dynamic meshing excitation of gears, and contact excitation of bearings, etc. Wide-band strong excitation acts on a multi degree of freedom nonlinear vibration system, and the transmission route and vibration phenomenon are complicated, vibration and noise issues are prominent. At the same time, the bending torsional coupled vibration, the box and shafts system coupled vibration, and the various modes coupled vibration of the transmission system will also generate strong dynamic loads, and even cause fatigue damage to parts and power interruptions in severe cases. Therefore, it is necessary to further study the vibration characteristics of the multi-stage planetary transmission system, especially the coupling mechanism of the vibration. Most previous researches are based on linear vibration theory or low degree of freedom systems, and less consideration is given to such multi degree of freedom nonlinear transmission systems with strong coupling. However, in multi degree of freedom nonlinear systems, the resonance phenomenon is complex and unavoidable, and under the action of multi-source wide-band strong excitation, multiple resonance phenomena such as main resonance and combined resonance may be induced, which is more complicated than simple systems. Therefore, it is also necessary to deeply study the coupling vibration mechanism of the system and suppress the system resonance. Based on the nonlinear factors such as tooth profile error, dynamic clearance, time-varying meshing stiffness and damping, manufacturing error, installation error, mass eccentricity and geometric eccentricity, a multi degree of freedom nonlinear transverse-torsional-pendulum coupled vibration model of single-stage planetary gear system is established. Under different working conditions, the vibration amplitude and phase of each component were studied, and the vibration form between each component was analyzed. Through frequency domain and time-frequency analysis of vibration response, the vibration coupling relationship between each direction and each component of the system under different working conditions is studied. Through the sensitivity analysis of the system parameters inertia, mass, stiffness of the supporting shaft and mesh stiffness, the key parameters which have great influence on the coupling vibration of the system are identified. The system coupling degree analysis standard of coupling vibration is established, and the influence rule of sensitive parameter change on coupling vibration is summarized. On the basis of coupling vibration analysis, this paper summarizes the coupling vibration analysis method of the system, and optimizes the system to achieve the purpose of vibration suppression."