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Examinando por Autor "MARISELA NICOLE FONSECA FUENTES"

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  • Imagen por defecto
    Publicación
    MULTINOMIAL LOGISTIC REGRESSION TO ESTIMATE AND PREDICT THE PERCEPTIONS OF INDIVIDUALS AND COMPANIES IN THE FACE OF THE COVID-19 PANDEMIC IN THE NUBLE REGION, CHILE
    (Sustainability, 2020)
    MARISELA NICOLE FONSECA FUENTES
    ;
    BENITO ELIOT UMAÑA HERMOSILLA
    THE CORONAVIRUS DISEASE 2019 (COVID-19) PANDEMIC IS TRANSFORMING THE WORLD WE LIVE IN, REVEALING OUR HEALTH, ECONOMIC, AND SOCIAL WEAKNESSES. IN THE LOCAL ECONOMY, THE LOSS OF JOB OPPORTUNITIES, THE UNCERTAINTY ABOUT THE FUTURE OF SMALL AND MEDIUM-SIZED COMPANIES AND THE DIFFICULTIES OF FAMILIES TO FACE THE EFFECTS OF THIS CRISIS, INVITE US TO INVESTIGATE THE PERCEPTION OF THE LOCAL COMMUNITY. BASED ON A QUESTIONNAIRE APPLIED TO 313 CITIZENS AND 51 COMPANIES, THIS STUDY EXPLORED THE PERCEPTION OF THESE ACTORS ON THE EFFECTS OF THE PANDEMIC AT THE LOCAL LEVEL AND DETERMINED THE MAIN FACTORS THAT INFLUENCED THEIR ASSESSMENT USING A MULTINOMIAL LOGISTIC REGRESSION MODEL. THE RESULTS INDICATED A SYSTEMATIC CONCERN FOR ISSUES OF EMPLOYMENT, JOB SECURITY, AND HOUSEHOLD DEBT. THE VARIABLES OF AGE AND SEX WERE SIGNIFICANT WHEN ANALYZING THE VULNERABILITY OF CERTAIN GROUPS, ESPECIALLY WOMEN AND THE ELDERLY, TO FACE THE EFFECTS OF THE CRISIS AND THEIR ROLE AS CITIZENS. AT THE BUSINESS LEVEL, THE FOCUS WAS ON ECONOMIC POLICIES THAT SUPPORT ITS OPERATIONAL CONTINUITY AND MANAGEMENT CAPACITY TO FACE A CHANGING SCENARIO.
  • Imagen por defecto
    Publicación
    MULTINOMIAL LOGISTIC REGRESSION TO ESTIMATE THE FINANCIAL EDUCATION AND FINANCIAL KNOWLEDGE OF UNIVERSITY STUDENTS IN CHILE
    (INFORMATION, 2021)
    MARISELA NICOLE FONSECA FUENTES
    ;
    BENITO ELIOT UMAÑA HERMOSILLA
    ALL INDIVIDUALS FACE DECISIONS DURING THEIR LIFETIME THAT DIRECTLY INFLUENCE THE ECONOMIC WELL-BEING OF THEIR FAMILIES. THEREFORE, FINANCIAL EDUCATION CAN BE A FUNDAMENTAL TOOL TO MAXIMIZE OUR ECONOMIC RESOURCES AND USE THEM WISELY. A VIRTUAL SURVEY WAS ADMINISTERED TO 410 VOLUNTEER STUDENTS BELONGING TO A PUBLIC UNIVERSITY IN SOUTHERN CHILE. THE OBJECTIVE WAS TO DETERMINE THE LEVEL OF FINANCIAL KNOWLEDGE AND APPRECIATION OF FINANCIAL EDUCATION OF FUTURE PROFESSIONALS. THE MOST IMPORTANT RESULTS DEMONSTRATE A REALITY IN WHICH YOUNG PEOPLE SAID THEY HAD THE HABIT OF SAVING AND BUDGETING AT HOME AND WERE RESPONSIBLE FOR PAYING THEIR BILLS ON TIME. HOWEVER, ONLY A VERY SMALL NUMBER OF PARTICIPANTS CLAIMED HAVING A SUPERIOR LEVEL OF KNOWLEDGE REGARDING FINANCIAL LITERACY. THE MAIN CHALLENGE FOR UNIVERSITIES IS TO INCLUDE THIS TOPIC IN THE ELECTIVE CURRICULUM OF ALL DEGREE PROGRAMS TO PROMOTE FINANCIAL CRITERION DEVELOPMENT THAT CONTRIBUTES TO THE COMPREHENSIVE TRAINING AND PROFESSIONAL COMPETENCIES OF FUTURE GRADUATES.
  • Imagen por defecto
    Publicación
    STOCHASTIC APPROACHES SYSTEMS TO PREDICTIVE AND MODELING CHILEAN WILDFIRES
    (MATHEMATICS, 2023)
    MARISELA NICOLE FONSECA FUENTES
    ;
    BENITO ELIOT UMAÑA HERMOSILLA
    WHETHER DUE TO NATURAL CAUSES OR HUMAN CARELESSNESS, FOREST FIRES HAVE THE POWER TO CAUSE DEVASTATING DAMAGE, ALTER THE HABITAT OF ANIMALS AND ENDEMIC SPECIES, GENERATE INSECURITY IN THE POPULATION, AND EVEN AFFECT HUMAN SETTLEMENTS WITH SIGNIFICANT ECONOMIC LOSSES. THESE NATURAL AND SOCIAL DISASTERS ARE VERY DIFFICULT TO CONTROL, AND DESPITE THE MULTIDISCIPLINARY HUMAN EFFORT, IT HAS NOT BEEN POSSIBLE TO CREATE EFFICIENT MECHANISMS TO MITIGATE THE EFFECTS, AND THEY HAVE BECOME THE NIGHTMARE OF EVERY SUMMER SEASON. THIS STUDY FOCUSES ON FORECAST MODELS FOR FIRE MEASUREMENTS USING TIME-SERIES DATA FROM THE CHILEAN MINISTRY OF AGRICULTURE. SPECIFICALLY, THIS STUDY PROPOSES A COMPREHENSIVE METHODOLOGY OF DETERMINISTIC AND STOCHASTIC TIME SERIES TO FORECAST THE FIRE MEASURES REQUIRED BY THE PROGRAMS OF THE NATIONAL FORESTRY CORPORATION (CONAF). THE MODELS USED IN THIS RESEARCH ARE AMONG THOSE COMMONLY APPLIED FOR TIME-SERIES DATA. FOR THE NUMBER OF FIRES SERIES, AN AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) MODEL IS SELECTED, WHILE FOR THE AFFECTED SURFACE SERIES, A SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) MODEL IS SELECTED, IN BOTH CASES DUE TO THE LOWEST ERROR METRICS AMONG THE MODELS FITTED. THE RESULTS PROVIDE EVIDENCE ON THE FORECAST FOR THE NUMBER OF NATIONAL FIRES AND AFFECTED NATIONAL SURFACE MEASURED BY A SERIES OF HECTARES (HA). FOR THE DETERMINISTIC METHOD, THE BEST MODEL TO PREDICT THE NUMBER OF FIRES AND AFFECTED SURFACE IS DOUBLE EXPONENTIAL SMOOTHING WITH DAMPED PARAMETER; FOR THE STOCHASTIC APPROACH, THE BEST MODEL FOR FORECASTING THE NUMBER OF FIRES IS AN ARIMA (2,1,2); AND FOR AFFECTED SURFACE, A SARIMA(1,1,0)(2,0,1)4, FORECASTING RESULTS ARE DETERMINED BOTH WITH STOCHASTIC MODELS DUE TO SHOWING A BETTER PERFORMANCE IN TERMS OF ERROR METRICS.

Concepción: Avda. Collao Nº 1202, Casilla 5-C - C.P: 4081112. Fono: +56-413111286

Chillán: Avda. Andrés Bello N° 720, Casilla 447 - C.P: 3800708. Fono: +56-422463000

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