Desviaciones al modelo logarítmico-lineal en la solubilidad de ibuprofén y naproxén en mezclas cosolventes propilenoglicol-agua

The deviations observed in the solubility of ibuprofen (IBP) and naproxen (NAP) in propylene glycol (PG) + water (W) cosolvent mixtures with respect to the logarithmic-linear model proposed by Yalkowsky have been analyzed at 25.00 ± 0.05 ºC. Negative deviations were obtained in all cosolvent compositions for both drugs; they were greater for IBP. Another treatment, based on Gibbs free energy relationships, was also employed showing an apparent hydrophobicity chameleonic effect, because at low PG proportions NAP is more hydrophobic, whereas at high PG proportions IBP is more hydrophobic. The results are discussed in terms of solute-solvent and solvent-solvent interactions.

Acidic dissolution of iron oxides and regeneration of a ceramic filter medium

The dewatering of iron ore concentrates requires large capacity in addition to producing a cake with low moisture content. Such large processes are commonly energy intensive and means to lower the specific energy consumption are needed. Ceramic capillary action disc filters incorporate a novel filter medium enabling the harnessing of capillary action, which results in decreased energy consumption in comparison to traditional filtration technologies. As another benefit, the filter medium is mechanically and chemically more durable than, for example, filter cloths and can, thus, withstand harsh operating conditions and possible regeneration better than other types of filter media. In iron ore dewatering, the regeneration of the filter medium is done through a combination of several techniques: (1) backwashing, (2) ultrasonic cleaning, and (3) acid regeneration. Although it is commonly acknowledged that the filter medium is affected by slurry particles and extraneous compounds, published research, especially in the field of dewatering of mineral concentrates, is scarce. Whereas the regenerative effect of backwashing and ultrasound are more or less mechanical, regeneration with acids is based on chemistry. The chemistry behind the acid regeneration is, naturally, dissolution. The dissolution of iron oxide particles has been extensively studied over several decades but those studies may not necessarily be directly applicable in the regeneration of the filter medium which has undergone interactions with the slurry components. The aim of this thesis was to investigate if free particle dissolution indeed correlates with the regeneration of the filter medium. For this purpose, both free particle dissolution and dissolution of surface adhered particles were studied. The focus was on acidic dissolution of iron oxide particles and on the study of the ceramic filter medium used in the dewatering of iron ore concentrates. The free particle dissolution experiments show that the solubility of synthetic fine grained iron oxide particles in oxalic acid could be explained through linear models accounting for the effects of temperature and acid concentration, whereas the dissolution of a natural magnetite is not so easily explained by such models. In addition, the kinetic experiments performed both support and contradict the work of previous authors: the suitable kinetic model here supports previous research suggesting solid state reduction to be the reaction mechanism of hematite dissolution but the formation of a stable iron oxalate is not supported by the results of this research. Several other dissolution mechanisms have also been suggested for iron oxide dissolution in oxalic acid, indicating that the details of oxalate promoted reductive dissolution are not yet agreed and, in this respect, this research offers added value to the community. The results of the regeneration experiments with the ceramic filter media show that oxalic acid is highly effective in removing iron oxide particles from the surface of the filter medium. The dissolution of those particles did not, however, exhibit the expected behaviour, i.e. complete dissolution. The results of this thesis show that although the regeneration of the ceramic filter medium with acids incorporates the dissolution of slurry particles from the surface of the filter medium, the regeneration cannot be assessed purely based upon free particle dissolution. A steady state, dependent on temperature and on the acid concentration, was observed in the dissolution of particles from the surface even though the limit of solubility of free iron oxide particles had not been reached. Both the regeneration capacity and efficiency, with regards to the removal of iron oxide particles, was found to be temperature dependent, but was not affected by the acid concentration. This observation further suggests that the removal of the surface adhered particles does not follow the dissolution of free particles, which do exhibit a dependency on the acid concentration. In addition, changes in the permeability and in the pore structure of the filter medium were still observed after the bulk concentration of dissolved iron had reached a steady state. Consequently, the regeneration of the filter medium continued after the dissolution of particles from the surface had ceased. This observation suggests that internal changes take place at the final stages of regeneration. The regeneration process could, in theory, be divided into two, possibly overlapping, stages: (1) dissolution of surface-adhered particles, and (2) dissolution of extraneous compounds from within the pore structure. In addition to the fundamental knowledge generated during this thesis, tools to assess the effects of parameters on the regeneration of the ceramic filter medium are needed. It has become clear that the same tools used to estimate the dissolution of free particles cannot be used to estimate the regeneration of a filter medium unless only a robust characterisation of the order of regeneration efficiency is needed.

Luottamuksen lähteet. Vertaileva tutkimus yleistynyttä luottamusta synnyttävistä mekanismeista

Tutkimuksen aiheena on yleistynyt luottamus. Väitöskirjassa tutkitaan mistä tuntemattomien kansalaisten toisiinsa kohdistama luottamus kumpuaa ja haetaan vastauksia tähän kysymykseen sekä maakohtaisen että vertailevan tutkimuksen avulla. Tutkimus koostuu yhteenvedon lisäksi viidestä tutkimusartikkelista, joissa luottamuksen syntyä tarkastellaan sekä yksilöiden mikrotason vuorovaikutuksen että maiden välisten eroavaisuuksien näkökulmasta. Yleistyneen luottamuksen synnystä on esitetty useita eri teorioita. Tässä tutkimuksessa tarkastellaan näistä kahta keskeisintä. Osa tutkijoista korostaa kansalaisyhteiskunnan ja ruohonjuuritason verkostojen roolia yleistyneen luottamuksen synnyn taustalla. Tämän hypoteesin mukaan kansalaiset, jotka viettävät aikaansa yhdistyksissä tai muissa sosiaalisissa verkostoissa, oppivat muita helpommin luottamaan paitsi täysin tuntemattomiin ihmisiin myös yhteiskunnallisiin instituutioihin (kansalaisyhteiskuntakeskeinen hypoteesi). Toiset taas painottavat yhteiskunnan julkisten instituutioiden merkitystä. Tämä hypoteesi korostaa instituutioiden reiluutta ja oikeudenmukaisuutta (instituutiokeskeinen hypoteesi). Ihmiset pystyvät luottamaan toisiinsa ja ratkaisemaan kollektiivisia ongelmiaan yhdessä silloin kun esimerkiksi poliittiset ja lainsäädännölliset instituutiot pystyvät luomaan tähän tarvittavan toimintaympäristön. Aineistoina käytetään kansallisia (Hyvinvointi- ja palvelut) sekä kansainvälisiä vertailevia kyselytutkimuksia (European Social Survey ja ISSP). Yksilö- ja makrotason analyyseja yhdistämällä selvitetään yleistynyttä luottamusta selittäviä tekijöitä sekä mekanismeja joiden kautta yleistynyt luottamus muodostuu. Väitöskirjan tulokset tukevat suurimmaksi osaksi instituutiokeskeiseen suuntaukseen sisältyviä hypoteeseja yleistyneen luottamuksen kasautumisesta. Kuitenkin myös esimerkiksi yhdistystoiminnalla havaittiin olevan joitakin yhdistysjäsenien ulkopuolelle ulottuvia myönteisiä vaikutuksia kansalaisten luottamukseen, mikä taas tukee kansalaisyhteiskuntakeskeistä hypoteesia. Tutkimuksen keskeinen tulos on, että kaiken kaikkiaan luottamus näyttäisi kukoistavan maissa, joissa kansalaiset kokevat julkiset instituutiot oikeudenmukaisina sekä reiluina, kansalaisyhteiskunnan roolin luottamuksen synnyttämisessä ollessa tälle alisteinen. Syyksi tähän on oletettu, että näissä maissa (erityisesti pohjoismaiset hyvinvointivaltiot) harjoitettu universaali hyvinvointipolitiikka ja palvelut ovat keskeisiä korkeaa yleistynyttä luottamusta selittäviä tekijöitä. Toisaalta maavertailuissa tätä yhteyttä on selitetty myös sillä, että näissä yhteiskunnassa ei ole paikannettavissa selkeää kulttuurisesti erottuvaa alaluokkaa. Tämän tutkimuksen tulokset tukevat enemmän universaalin hyvinvointivaltion oikeudenmukaisuuteen liittyviä ominaisuuksia alaluokkaistumishypoteesin sijaan. Toisaalta mikrotasolla tarkasteltuna yleistyneen luottamuksen ja hyvinvointipalvelujen välinen yhteys liittyy enemmän palveluiden riittävyyteen kuin niiden universaalisuuden asteeseen. Niin ikään maavertailuissa esimerkiksi verotuksen oikeudenmukaisena kokeminen näyttäisi olevan palvelujen saatavuutta tai niihin liittyviä oikeudenmukaisuuden kokemuksia tärkeämpi seikka yleistyneen luottamuksen kannalta.

Whole transcriptome organisation in the dehydrated supraoptic nucleus

The supraoptic nucleus (SON) is part of the central osmotic circuitry that synthesises the hormone vasopressin (Avp) and transports it to terminals in the posterior lobe of the pituitary. Following osmotic stress such as dehydration, this tissue undergoes morphological, electrical and transcriptional changes to facilitate the appropriate regulation and release of Avp into the circulation where it conserves water at the level of the kidney. Here, the organisation of the whole transcriptome following dehydration is modelled to fit Zipf's law, a natural power law that holds true for all natural languages, that states if the frequency of word usage is plotted against its rank, then the log linear regression of this is -1. We have applied this model to our previously published euhydrated and dehydrated SON data to observe this trend and how it changes following dehydration. In accordance with other studies, our whole transcriptome data fit well with this model in the euhydrated SON microarrays, but interestingly, fit better in the dehydrated arrays. This trend was observed in a subset of differentially regulated genes and also following network reconstruction using a third-party database that mines public data. We make use of language as a metaphor that helps us philosophise about the role of the whole transcriptome in providing a suitable environment for the delivery of Avp following a survival threat like dehydration.

Instrumental color and sensory acceptance of soy-based emulsions: a response surface approach

Response Surface Methodology (RSM) was applied to evaluate the chromatic features and sensory acceptance of emulsions that combine Soy Protein (SP) and red Guava Juice (GJ). The parameters analyzed were: instrumental color based on the coordinates a* (redness), b* (yellowness), L* (lightness), C* (chromaticity), h* (hue angle), visual color, acceptance, and appearance. The analyses of the results showed that GJ was responsible for the high measured values of red color, hue angle, chromaticity, acceptance, and visual color, whereas SP was the variable that increased the yellowness intensity of the assays. The redness (R²adj = 74.86%, p < 0.01) and hue angle (R²adj = 80.96%, p < 0.01) were related to the independent variables by linear models, while the sensory data (color and acceptance) could not be modeled due to a high variability. The models of yellowness, lightness, and chromaticity did not present lack of fit but presented adjusted determination coefficients bellow 70%. Notwithstanding, the linear correlations between sensory and instrumental data were not significant (p > 0.05) and low Pearson coefficients were obtained. The results showed that RSM is a useful tool to develop soy-based emulsions and model some chromatic features of guava-based emulsions through RSM.

Influence of process parameters on the color and texture of passion fruit albedo preserved in syrup

The industrialization of passion fruit in the form of juice produces considerable amounts of residue that could be used as food. The objective of the present study was to determine the effects of the volume of passion fruit juice added to the syrup and the cooking time on the color and texture of passion fruit albedo preserved in syrup. Multi-linear models were well fit to describe the value for a* (for the albedo) the values for b* (for the albedo and syrup), which exhibited high correlation coefficients of 98%, 84%, and 88%, respectively. The volume of passion fruit juice added and the cooking time of the albedos in the syrup, involved in the processing of passion fruit albedo preserves in syrup, significantly affected color analyses. The texture was not affected by the parameters studied. Therefore, the use of larger volumes of passion fruit juice and longer cooking time is recommended for the production of passion fruit albedo preserves in syrup to achieve the characteristic yellow color of the fruit.

Modeling Energy Futures Returns With Markov Regime Switching Model

Financial time series have a tendency of abruptly changing their behavior and maintain this behavior for several consecutive periods, and commodity futures returns are not an exception. This quality proposes that nonlinear models, as opposed to linear models, can more accurately describe returns and volatility. Markov regime switching models are able to match this behavior and have become a popular way to model financial time series. This study uses Markov regime switching model to describe the behavior of energy futures returns on a commodity level, because studies show that commodity futures are a heterogeneous asset class. The purpose of this thesis is twofold. First, determine how many regimes characterize individual energy commodities’ returns in different return frequencies. Second, study the characteristics of these regimes. We extent the previous studies on the subject in two ways: We allow for the possibility that the number of regimes may exceed two, as well as conduct the research on individual commodities rather than on commodity indices or subgroups of these indices. We use daily, weekly and monthly time series of Brent crude oil, WTI crude oil, natural gas, heating oil and gasoil futures returns over 1994–2014, where available, to carry out the study. We apply the likelihood ratio test to determine the sufficient number of regimes for each commodity and data frequency. Then the time series are modeled with Markov regime switching model to obtain the return distribution characteristics of each regime, as well as the transition probabilities of moving between regimes. The results for the number of regimes suggest that daily energy futures return series consist of three to six regimes, whereas weekly and monthly returns for all energy commodities display only two regimes. When the number of regimes exceeds two, there is a tendency for the time series of energy commodities to form groups of regimes. These groups are usually quite persistent as a whole because probability of a regime switch inside the group is high. However, individual regimes in these groups are not persistent and the process oscillates between these regimes frequently. Regimes that are not part of any group are generally persistent, but show low ergodic probability, i.e. rarely prevail in the market. This study also suggests that energy futures return series characterized with two regimes do not necessarily display persistent bull and bear regimes. In fact, for the majority of time series, bearish regime is considerably less persistent. Rahoituksen aikasarjoilla on taipumus arvaamattomasti muuttaa käyttäytymistään ja jatkaa tätä uutta käyttäytymistä useiden periodien ajan, eivätkä hyödykefutuurien tuotot tee tähän poikkeusta. Tämän ominaisuuden johdosta lineaaristen mallien sijasta epälineaariset mallit pystyvät tarkemmin kuvailemaan esimerkiksi tuottojen jakauman parametreja. Markov regiiminvaihtomallit pystyvät vangitsemaan tämän ominaisuuden ja siksi niistä on tullut suosittuja rahoituksen aikasarjojen mallintamisessa. Tämä tutkimus käyttää Markov regiiminvaihtomallia kuvaamaan yksittäisten energiafutuurien tuottojen käyttäytymistä, sillä tutkimukset osoittavat hyödykefutuurien olevan hyvin heterogeeninen omaisuusluokka. Tutkimuksen tarkoitus on selvittää, kuinka monta regiimiä tarvitaan kuvaamaan energiafutuurien tuottoja eri tuottofrekvensseillä ja mitkä ovat näiden regiimien ominaisuudet. Aiempaa tutkimusta aiheesta laajennetaan määrittämällä regiimien lukumäärä tilastotieteellisen testauksen menetelmin sekä tutkimalla energiafutuureja yksittäin; ei indeksi- tai alaindeksitasolla. Tutkimuksessa käytetään päivä-, viikko- ja kuukausiaikasarjoja Brent-raakaöljyn, WTI-raakaöljyn, maakaasun, lämmitysöljyn ja polttoöljyn tuotoista aikaväliltä 1994–2014, siltä osin kuin aineistoa on saatavilla. Likelihood ratio -testin avulla estimoidaan kaikille aikasarjoille regiimien määrä,jonka jälkeen Markov regiiminvaihtomallia hyödyntäen määritetään yksittäisten regiimientuottojakaumien ominaisuudet sekä regiimien välinen transitiomatriisi. Tulokset regiimien lukumäärän osalta osoittavat, että energiafutuurien päiväkohtaisten tuottojen aikasarjoissa regiimien lukumäärä vaihtelee kolmen ja kuuden välillä. Viikko- ja kuukausituottojen kohdalla kaikkien energiafutuurien prosesseissa regiimien lukumäärä on kaksi. Kun regiimejä on enemmän kuin kaksi, on prosessilla taipumus muodostaa regiimeistä koostuvia ryhmiä. Prosessi pysyy ryhmän sisällä yleensä pitkään, koska todennäköisyys siirtyä ryhmään kuuluvien regiimien välillä on suuri. Yksittäiset regiimit ryhmän sisällä eivät kuitenkaan ole kovin pysyviä. Näin ollen prosessi vaihtelee ryhmän sisäisten regiimien välillä tiuhaan. Regiimit, jotka eivät kuulu ryhmään, ovat yleensä pysyviä, mutta prosessi ajautuu niihin vain harvoin, sillä todennäköisyys siirtyä muista regiimeistä niihin on pieni. Tutkimuksen tulokset osoittavat myös, että prosesseissa, joita ohjaa kaksi regiimiä, nämä regiimit eivät välttämättä ole pysyvät bull- ja bear-markkinatilanteet. Tulokset osoittavat sen sijaan, että bear-markkinatilanne on energiafutuureissa selvästi vähemmän pysyvä.

Vigor and field emergence in "high oleic" sunflower seeds, in southeast of Buenos Aires province

Sunflower crop was based, as yet, on high linoleic cultivars, but in the last years request for oil with higher content of oleic acid has increased, due to their dietary characteristics. At the beginning, high oleic cultivars were used to be sown in warm regions, but then the concern about growing it in temperate areas, as the south-east of Buenos Aires Province, was posed. In this region, early sowings are recommended, so that grain filling matches with a period of appropriate hydric and light conditions, as to result in greater yields. However, early sowings are limited by low soil temperature, that delays seedling emergence, resulting in heterogeneous stand establishment. The aim of this work was to evaluate seed performance of four high oleic cultivars in the southern area of Buenos Aires Province, by means of vigor tests and field trials. Germination, cold, tetrazolium viability, tetrazolium viability with cold, accelerated ageing tests and three field sowings at different soil temperatures were performed. Data were analyzed by Anova using generalised linear models, and tests and cultivars were contrasted among themselves. Similar seedling emergence under optimal and suboptimal temperatures for high oleic and high linoleic cultivars was recorded. The success of seedling establishment does not appear to be related to the acidic composition of seeds.

A sequential analysis of therapist scaffolding and child concept formation in narrative therapy

Narrative therapy is a postmodern therapy that takes the position that people create self-narratives to make sense of their experiences. To date, narrative therapy has compiled virtually no quantitative and very little qualitative research, leaving gaps in almost all areas of process and outcome. White (2006a), one of the therapy's founders, has recently utilized Vygotsky's (1934/1987) theories of the zone of proximal development (ZPD) and concept formation to describe the process of change in narrative therapy with children. In collaboration with the child client, the narrative therapist formalizes therapeutic concepts and submits them to increasing levels of generalization to create a ZPD. This study sought to determine whether the child's development proceeds through the stages of concept formation over the course of a session, and whether therapists' utterances scaffold this movement. A sequential analysis was used due to its unique ability to measure dynamic processes in social interactions. Stages of concept formation and scaffolding were coded over time. A hierarchical log-linear analysis was performed on the sequential data to develop a model of therapist scaffolding and child concept development. This was intended to determine what patterns occur and whether the stated intent of narrative therapy matches its actual process. In accordance with narrative therapy theory, the log-linear analysis produced a final model with interactions between therapist and child utterances, and between both therapist and child utterances and time. Specifically, the child and youth participants in therapy tended to respond to therapist scaffolding at the corresponding level of concept formation. Both children and youth and therapists also tended to move away from earlier and toward later stages of White's scaffolding conversations map as the therapy session advanced. These findings provide support for White's contention that narrative therapists promote child development by scaffolding child concept formation in therapy.

The Seemingly Unrelated Dynamic Cointegration Regression Model and Testing for Purching Power Parity.

This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. Simulation results suggest that this new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of purchasing power parity (PPP) among the G-7 countries. The test based on the efficient estimates rejects the PPP hypothesis for most countries.

Semi-Parametric Weak Instrument Regressions with an Application to the Risk-Return Trade-off

Recent work shows that a low correlation between the instruments and the included variables leads to serious inference problems. We extend the local-to-zero analysis of models with weak instruments to models with estimated instruments and regressors and with higher-order dependence between instruments and disturbances. This makes this framework applicable to linear models with expectation variables that are estimated non-parametrically. Two examples of such models are the risk-return trade-off in finance and the impact of inflation uncertainty on real economic activity. Results show that inference based on Lagrange Multiplier (LM) tests is more robust to weak instruments than Wald-based inference. Using LM confidence intervals leads us to conclude that no statistically significant risk premium is present in returns on the S&P 500 index, excess holding yields between 6-month and 3-month Treasury bills, or in yen-dollar spot returns.

Altruism, Intergenerational Transfers of Time and Bequests

This paper uses a standard two-period overlapping generation model to examine the behavior of an economy where both intergenerational transfers of time and bequests are available. While bequests have been examined extensively, time transfers have received little or no attention in the literature. Assuming a log-linear utility function and a Cobb-Douglas production function, we derive an explicit solution for the dynamics and show that altruistic intergenerational time transfers can take place in presence of a binding non-negativity constraint on bequests. We also show that with either type of transfers capital is an increasing function of the intergenerational degree of altruism. However, while with time transfers the labor supply of the young increases with the degree of altruism, with bequests it may decrease

L’arbre de régression multivariable et les modèles linéaires généralisés revisités : applications à l’étude de la diversité bêta et à l’estimation de la biomasse d’arbres tropicaux

En écologie, dans le cadre par exemple d’études des services fournis par les écosystèmes, les modélisations descriptive, explicative et prédictive ont toutes trois leur place distincte. Certaines situations bien précises requièrent soit l’un soit l’autre de ces types de modélisation ; le bon choix s’impose afin de pouvoir faire du modèle un usage conforme aux objectifs de l’étude. Dans le cadre de ce travail, nous explorons dans un premier temps le pouvoir explicatif de l’arbre de régression multivariable (ARM). Cette méthode de modélisation est basée sur un algorithme récursif de bipartition et une méthode de rééchantillonage permettant l’élagage du modèle final, qui est un arbre, afin d’obtenir le modèle produisant les meilleures prédictions. Cette analyse asymétrique à deux tableaux permet l’obtention de groupes homogènes d’objets du tableau réponse, les divisions entre les groupes correspondant à des points de coupure des variables du tableau explicatif marquant les changements les plus abrupts de la réponse. Nous démontrons qu’afin de calculer le pouvoir explicatif de l’ARM, on doit définir un coefficient de détermination ajusté dans lequel les degrés de liberté du modèle sont estimés à l’aide d’un algorithme. Cette estimation du coefficient de détermination de la population est pratiquement non biaisée. Puisque l’ARM sous-tend des prémisses de discontinuité alors que l’analyse canonique de redondance (ACR) modélise des gradients linéaires continus, la comparaison de leur pouvoir explicatif respectif permet entre autres de distinguer quel type de patron la réponse suit en fonction des variables explicatives. La comparaison du pouvoir explicatif entre l’ACR et l’ARM a été motivée par l’utilisation extensive de l’ACR afin d’étudier la diversité bêta. Toujours dans une optique explicative, nous définissons une nouvelle procédure appelée l’arbre de régression multivariable en cascade (ARMC) qui permet de construire un modèle tout en imposant un ordre hiérarchique aux hypothèses à l’étude. Cette nouvelle procédure permet d’entreprendre l’étude de l’effet hiérarchisé de deux jeux de variables explicatives, principal et subordonné, puis de calculer leur pouvoir explicatif. L’interprétation du modèle final se fait comme dans une MANOVA hiérarchique. On peut trouver dans les résultats de cette analyse des informations supplémentaires quant aux liens qui existent entre la réponse et les variables explicatives, par exemple des interactions entres les deux jeux explicatifs qui n’étaient pas mises en évidence par l’analyse ARM usuelle. D’autre part, on étudie le pouvoir prédictif des modèles linéaires généralisés en modélisant la biomasse de différentes espèces d’arbre tropicaux en fonction de certaines de leurs mesures allométriques. Plus particulièrement, nous examinons la capacité des structures d’erreur gaussienne et gamma à fournir les prédictions les plus précises. Nous montrons que pour une espèce en particulier, le pouvoir prédictif d’un modèle faisant usage de la structure d’erreur gamma est supérieur. Cette étude s’insère dans un cadre pratique et se veut un exemple pour les gestionnaires voulant estimer précisément la capture du carbone par des plantations d’arbres tropicaux. Nos conclusions pourraient faire partie intégrante d’un programme de réduction des émissions de carbone par les changements d’utilisation des terres.

Tests pour la dépendance entre les sections dans un modèle de Poisson

Les simulations et figures ont été réalisées avec le logiciel R.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.