Search results for "Autore"
showing 10 items of 352 documents
Forecasting Electricity Consumption and Production in Smart Homes through Statistical Methods
2022
Abstract Over the last years, a steady increase in both domestic electricity consumption and in the adoption of personal clean energy production systems has been observed worldwide. By analyzing energy consumption and production on photovoltaic panels mounted in a house, this work focuses on finding patterns in electrical energy consumption and devising a predictive model. Our goal is to find an accurate method to predict electrical energy consumption and production. Being able to anticipate how consumers will use energy in the near future, homeowners, companies and governments may optimize their behavior and the import and export of electricity. We evaluated the ARIMA and TBATS statistical…
La percezione dei docenti di insegnamento-apprendimento nel periodo emergenziale COVID-19: una ricerca nella Scuola Siciliana
2021
La didattica a distanza nel periodo di emergenza COVID-19 ha rappresentato una novità senza precedenti cui docenti e studenti non erano preparati. L’indagine sull'esperienza di 1364 insegnanti siciliani ha consentito di raccogliere informazioni sulle strategie organizzative e didattiche attivate, sulle criticità e sulla valutazione dell'efficacia didattica degli interventi effettuati. Sono state rilevate in modo sistematico le percezioni dei docenti relative all’autoregolazione e in particolare alla pianificazione, alle strategie di gestione delle informazioni, di correzione, e di valutazione. La ricerca nasce dal desiderio di accrescere la consapevolezza dei docenti. Conoscere gli effett…
Next-Day Bitcoin Price Forecast
2019
This study analyzes forecasts of Bitcoin price using the autoregressive integrated moving average (ARIMA) and neural network autoregression (NNAR) models. Employing the static forecast approach, we forecast next-day Bitcoin price both with and without re-estimation of the forecast model for each step. For cross-validation of forecast results, we consider two different training and test samples. In the first training-sample, NNAR performs better than ARIMA, while ARIMA outperforms NNAR in the second training-sample. Additionally, ARIMA with model re-estimation at each step outperforms NNAR in the two test-sample forecast periods. The Diebold Mariano test confirms the superiority of forecast …
'Dual' Gravity: Using Spatial Econometrics to Control for Multilateral Resistance
2010
We propose a quantity-based `dual' version of the gravity equation that yields an estimating equation with both cross-sectional interdependence and spatially lagged error terms. Such an equation can be concisely estimated using spatial econometric techniques. We illustrate this methodology by applying it to the Canada-U.S. data set used previously, among others, by Anderson and van Wincoop (2003) and Feenstra (2002, 2004). Our key result is to show that controlling directly for spatial interdependence across trade flows, as suggested by theory, significantly reduces border effects because it captures `multilateral resistance'. Using a spatial autoregressive moving average specification, we …
Dopamine Autoreceptor Agonists in the Treatment of Schizophrenia and Major Depression*
1992
Dopamine autoreceptor agonists reduce the firing rate, synthesis, and release of dopamine in dopaminergic neurons by means of a negative feedback mechanism via stimulation of autoreceptors. Moreover, dopamine autoreceptor agonists are able to stimulate supersensitive but not normosensitive postsynaptic receptors. For dopamine autoreceptor agonists, therapeutic effects by readjustment of excessive or deficient dopaminergic function have been postulated for positive and negative schizophrenic symptomatology as well as for subtypes of depressive disorders. Investigations on the therapeutic effects of autoreceptor-nonselective dopamine agonists in schizophrenia or depression have yielded incons…
Il Filtro Integrale Auto-Regressivo Continuo (I-ARC) per l’Analisi di Strutture Esposte al Vento
2010
In questo studio viene proposto un metodo per la rappresentazione di processi aleatori Gaussiani e stazionari, utile a modellare la turbolenza della velocità del vento, introducendo la versione integrale del modello auto-regressivo discreto già proposto in precedenza. La rappresentazione di un processo aleatorio di assegnata funzione di correlazione viene condotta integrando un’equazione integro-differenziale in cui viene coinvolto un nucleo, che rappresenta la memoria del processo, in presenza di un rumore bianco Gaussiano. La soluzione dell’equazione rappresenta un campione del processo aleatorio della turbolenza della velocità del vento. E’ stato mostrato che il modello I-ARC fornisce, n…
Džan Ailin dzīves gājums un tā atspoguļojums viņas literārajos darbos
2019
Džan Ailin ir izcila ķīniešu rakstniece, kura dzīvoja 1920.-1995. gados. Dzimusi aristokrātiskā ģimenē, rakstniece bija radīta, lai dzīvotu labu dzīvi. Bet jau agrā jaunībā meitene saprata, ka viņas dzīve nebūs viegla. Tēvs bija opija atkarīgais un māte pameta savus bērnus, lai dotos uz Franciju, jo viņas vīrs bija apņēmis mīļāko. Jaunā meitene dzīves laikā piedzīvoja dažādas nelaimes un grūtības, bet viņa iemācījās no visām šīm likstām un ķibelēm. Džan Ailin sāka padziļināti studēt ķīniešu valodu un literatūru, kā arī angļu valodu un literatūru, kas palīdzēja izveidot rakstnieces unikālo stilu, kur viņa saglabāja Ķīnas tradicionālās literatūras elementus un pievienoja tiem rietumu stilu un…
VAR modeļu un kointegrācijas analīzes pielietojums zelta cenas analīzē
2017
Darbs tiek veltīts kointegrācijai un kļūdas korekcijas modelim. Darbā dots ieskats par vienības saknes testiem, vektoru autoregresijas vienādojumiem, kointegrāciju, kļūdu korekciju modeļiem. Metodes tika pielietotas pētot sakarības starp tādiem valūtu pāriem kā zelts pret ASV dolāru (XAU/USD) un Šveices franks pret ASV dolāru (CHF/USD). Ar Engla-Greinžera un Johansena metodēm parādīts, ka periodā no 2011. gada maija līdz 2016. gada decembrim pastāv kointegrācija starp iepriekš minētajiem instrumentiem.
Impact of COVID-19 on the travel and tourism industry.
2021
Abstract Our paper is among the first to measure the potential effects of the COVID-19 pandemic on the tourism industry. Using panel structural vector auto-regression (PSVAR) (Pedroni, 2013) on data from 1995 to 2019 in 185 countries and system dynamic modeling (real-time data parameters connected to COVID-19), we estimate the impact of the pandemic crisis on the tourism industry worldwide. Past pandemic crises operated mostly through idiosyncratic shocks' channels, exposing domestic tourism sectors to large adverse shocks. Once domestic shocks perished (zero infection cases), inbound arrivals revived immediately. The COVID-19 pandemic, however, is different; and recovery of the tourism ind…
Holidays, weekends and range-based volatility
2020
Abstract This study analyses the effect of non-trading periods on the forecasting ability of S&P500 index range-based volatility models. We find that volatility significantly diminishes on the first trading day after holidays and weekends, but not after long weekends. Our findings indicate that models that include autoregressive terms that interact with dummies that allow us to capture changes in volatility levels after interrupting periods provide greater explanatory power than simple autoregressive models. Therefore, the shorter the length of the non-trading periods between two trading days, the higher the overestimation of the volatility if this effect is not considered in volatility for…