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1
artículo
It is a fact well documented by economic theory that high and durable inflation has a negative effect on economic growth, but that as the effects on the latter decline, they are non-linear. This work answers two research questions related to the works that have studied this empirical relationship in the last three decades. The first is about its external validity: How useful are they to predict the economic evolution of emerging countries? Simulating the growth of a sample of emerging markets for the past 20 years from these models, we found high and disparate prediction errors and therefore certain drawbacks when generalizing their conclusions. Understanding why this happens gives rise to the second question, linked to the internal validity of the models: What unresolved problems exist in the estimates carried out by the authors? the answer is that there are problems of specification,...
2
artículo
The companies increasingly interact with clients and providers. This situation requires adequate risk ma-nagement to prevent situations of financial distress. A company is technically insolvent when it has enough cash to make immediate payments. Therefore, one of the points to study is the financial solvency and risk to the bankruptcy of its customer base. To this end, there are techniques to measure the possibility of insolvency of a company. The most reliable is the Altman Z model, which is based on the statistical technique of Multiple Discriminant Analysis. This model uses financial ratios to determine the financial risk and predict whether a company is healthy from a financial point of view, or is on its way to become insolvent. The results found by Altman and revision of the original model proposed by him is presented.
3
artículo
Publicado 2022
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In order to determine the contribution of the sociodemographic, psychosocial and health variables to a prediction model of dementia in the elderly population, a secondary analysis was carried out with the data from the “Health, Well-being and Aging. Bogotá, 2012”, with 2000 men and women over 60 years of age from urban and rural areas of Bogotá. To select the sample, a probabilistic, multistage, conglomerate and stratified sampling was carried out, based on the 2005 National Census. The SABE questionnaire adapted for Colombia was used. According to the level of measurement of each variable and the distribution of the data, univariate and bivariate analyzes were performed, with dementia as a criterion variable and sociodemographic and health variables as predictors; 30 variables were included. It was found that 40.1% of the variance of dementia is explained by age, educational ...
4
artículo
Desertion is a problem that affects public and private universities, and leads to a series of negative consequences for both institutions and students. Therefore, the objective of this study was to determine how the use of predictive models in low pass-rate courses helps to identify students at risk of desertion. Seven predictive models were designed using CRISP (Cross- Industry Standard Process for Data Mining) methodology and students’ academic records to be applied in seven low pass-rate courses. Among the main results, it can be noted that predictive models contributed to the reduction of fail rates by 25% and 40%, and that the variables that best forecast desertion were career choice (vocation), number of times students enrolled in the course, and grades obtained in mathematics or language arts when students attended the fifth year of high school.
5
artículo
Publicado 1999
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ARIMA univariate time series analysis were used for modeling and forecasting future energy production and consumption in Asturias-Spain. Initially, each series was recorder monthly from 1980 to 1996. These data include trend and seasonal variations wich allow the use of ARIMA (AutoRegressive Integrated Moving Average) univariate models for predictions of future behavioral patterns. The optimum forecasting models obtained for each energetic series, have a satisfactory degree of statistical validity (Low approximation errors) and are suitable for use as reference inputs in the Regional Energetic Plan of Asturias.
6
artículo
Publicado 2025
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Objective: This study analyzes how predictive models and AI algorithms influence fashion electronic trade optimization, assessing their impact on personalizing the user experience and increasing sales. Materials and methods: A quantitative approach with a non-experimental, cross-sectional, and correlational design was used, applying surveys to 50 fashion retail companies with an online presence, and to 500 consumers active on electronic trade platforms. Data were collected through surveys and databases, analyzing factors such as the implementation of artificial intelligence, the conversion rate, and the customer loyalty. For the analysis, descriptive and inferential statistics tests, including correlation and regression analysis, were used for the analysis. Results: The results evidence that AI has a significant impact on sales and customer loyalty, with a positive correlation (r = 0.87;...
7
artículo
Publicado 2012
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El presente artículo tiene como fi nalidad mostrar una metodología para la comparación de los modelos de clasificación “regresión logística” y “árbol de clasificación”. Este análisis comparativo se basó en el estudio de la deserción universitaria en una universidad particular. Se deseaba determinar si un alumno dado podría ser clasifi cado como un desertor potencial, teniendo como referencia determinadas variables explicativas. Para la aplicación de los modelos de clasificación se hizo uso del software comercial Minitab 16 y del software libre Weka 3-7-2, en los que se obtuvieron los modelos de regresión logística y el árbol de clasificación, respectivamente. En ambos casos se usaron los mismos datos de entrada y los datos de prueba para su evaluación. Entre las principales conclusiones se puede señalar que los dos modelos presentaron resultados similares, de ...
8
artículo
Publicado 2019
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Cervical cancer is currently the fourth most frequent type of cancer in women. A large number of techniques from the Artificial Intelligence (AI) such as Neuronal Networks, Support Vector Machines (SVM), Decision Trees and others; have been used to deal with the problem of predicting this disease. The following paper shows the cervical cancer risk prediction, by implementing a probabilistic model based on Bayesian Networks and using 322 instances where we could retrieve 15 different features that are known information from each patient. The tests were made using the 40% of the whole dataset, confusion matrix and AUC indicator. The results show that this work has raised a 96% of success rate as well as 0.9864 in terms of the AUC indicator, in addition to this, the results suggest that Bayesian Networks are able to reach a high performance and provide transparency during the inference proc...
9
artículo
Publicado 2019
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Objective. To determine the predictive factors of mortality in patients with shock who live at high altitude at more than 3250 m.a.s.l. Methods. A prospective, observational and descriptive study was conducted between December 2015 and March 2016, at two Hospitals in Huancayo, Peru. We included 46 patients diagnosed with distributive, hypovolemic or cardiogenic shock. The data collection instrument was a questionnaire. For the statistical analysis, binary and multiple logistic regression were used. It was considered significant p <0.05. Results. The average age was 67 +/- 18 years (range: 9 to 95); 25 (54.3 %) were male and 21 (47.3 %) female. 32 (69.5 %) patients died. The average age of deaths was 70.3 +/- 9.6 years and survivors 50.4 +/- 4.2 years; the most frequent type of shock was distributive and the most common comorbidities were respiratory failure, high blood pressure, and d...
10
artículo
Publicado 2021
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The results of 4 predictive models, logistic regression, decision trees, KNN and a neural network are compared to predict the academic dropout of students at the National Intercultural University of the Amazon, applied to a dataset extracted from the system's database. of academic management of the university, which contains socioeconomic and academic performance data which were processed and formatted using onehotencoding techniques in order to apply the predictive models already mentioned. For data processing and formatting, Transac Sql queries were used and the application of predictive models was done through Knime Software and using Python through Google Colab. The results obtained by applying 4 predictive models are very good since they all exceeded 80% of Accuracy, which guarantees that they can be put into production for the benefit of the university and thus can make better deci...
11
artículo
Publicado 2019
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Objective. To determine the predictive factors of mortality in patients with shock who live at high altitude at more than 3250 m.a.s.l. Methods. A prospective, observational and descriptive study was conducted between December 2015 and March 2016, at two Hospitals in Huancayo, Peru. We included 46 patients diagnosed with distributive, hypovolemic or cardiogenic shock. The data collection instrument was a questionnaire. For the statistical analysis, binary and multiple logistic regression were used. It was considered significant p <0.05. Results. The average age was 67 +/- 18 years (range: 9 to 95); 25 (54.3 %) were male and 21 (47.3 %) female. 32 (69.5 %) patients died. The average age of deaths was 70.3 +/- 9.6 years and survivors 50.4 +/- 4.2years; the most frequent type of shock was distributive and the most common comorbidities were respiratory failure, high blood pressure, and di...
12
tesis de grado
Publicado 2018
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Este trabajo de investigación desarrolla un modelo predictivo automatizado para la planificación de la producción de arroz en la región San Martín, para ello, se ha analizado la información histórica de la producción de arroz en la región San Martín, desde el año 1990 hasta el año 2013. Se ha analizado técnicas de regresión lineal y polinomial, tomando este último como modelo para predecir la producción de arroz hasta en un escenario futuro de 5 años. Este resulta muy eficiente porque considera las fluctuaciones de la producción arrocera en periodos de largo plazo. El objetivo de esta investigación fue desarrollar un modelo predictivo automatizado para planificar mejor la producción de arroz en la región San Martín, ya que el margen de error en la predicción de la producción de arroz es considerado como demasiado impreciso e inexacto por los colaboradores de nivel...
13
artículo
Publicado 2022
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Background: It is essential to identify the epidemiological and clinical characteristics of patients infected with COVID-19 associated with disease progression leading to ICU admission. The objective was to systematically review the models or scores for predicting admission to the intensive care unit (ICU) available to date for patients with COVID-19. Methods: The study is a systematic review. PubMed, Scopus, Web of Science, Ovid-Medline, and Embase were searched until July 13, 2022. We included studies that have developed and validated a model or scoring system to predict ICU admission in patients with COVID-19. The primary outcome was ICU admission. Risk of bias assessment was performed using the PROBAST tool which is based on four domains: participants, predictors, outcome and analysis. Results: Two studies were included for data extraction and critical appraisal. Predictive models of...
14
artículo
Publicado 2023
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What do we mean when we say that algorithms are capable of predicting what is going to happen and anticipating our actions? In the following article I will analyse the phenomena of algorithmic prediction and behavioural anticipation, explaining their convergence in contemporary techniques of predictive analytics. First, I will deal with some possible misconceptions about the predictive capacities of algorithms by delving into probability theory. Secondly, I will take Bernard Stiegler’s post-phenomenological theory of algorithmic governmentality as a model to explain their capacity for behavioural anticipation. Lastly, I will present Mark Hansen’s Whiteheadian reading of predictive analytics, in which he provides a way to understand the ontological basis of the power of these algorithmic systems and also highlight their epistemological limits. Besides the theoretical purposiveness of ...
15
artículo
Publicado 2018
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La deserción es un problema que afecta a las universidades, públicas y privadas, y acarrea una serie de consecuencias negativas tanto para las instituciones como para los mismos jóvenes, por ello, el objetivo de este estudio fue determinar cómo el uso de modelos predictivos en asignaturas críticas contribuye a identificar a los estudiantes en riesgo de deserción. Se diseñaron siete modelos predictivos con la metodología CRISP (Cross-Industry Standard Process for Data Mining) y el historial académico de los estudiantes, para ser aplicados en siete cursos. Entre los principales resultados se puede destacar que los modelos predictivos contribuyeron a reducir en un 25 % y 40 % los niveles de desaprobación y las variables que mejor la predijeron fueron la carrera que estudian (vocación), el número de veces que se matriculan en la asignatura y la nota que tuvieron en matemática o ...
16
tesis doctoral
Publicado 2023
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State-of-the-art control and robotics challenges have long been tackled using model-based control methods like model predictive control (MPC) and reinforcement learning (RL). These methods excel in complex dynamic domains, such as manipulation tasks, but struggle with real-world issues like wear-and-tear, uncalibrated sensors, and misspecifications. These factors often perturb system dynamics, leading to the 'reality gap' problem when robots transition from simulations to real-world environments. This work aims to bridge this gap by combining RL and control in a learning framework that adapts MPC to robot decisions, optimizing performance despite uncertainties in dynamics model parameters. This thesis presents three key contributions to robotics control. The first is a novel reward-based framework for refining stochastic Model Predictive Control (MPC). It utilizes Bayesian Optimization (...
17
artículo
Publicado 2023
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Objective. To evaluate the concurrent, predictive validity and reliability of an algorithm designed to determine the stage of change for HIV testing. Methods. A cross-sectional, correlational, two-stage study was conducted. The first, with 300 young university students, to evaluate the concurrent and predictive criterion validity with variables such as self-efficacy, knowledge about HIV testing and risk perception, measured with instruments that present Cronbach's a between ,73 and ,93. The second in 75 migrants, considered as at-risk population (n = 75), to assess reliability by means of a test-retest. Results. The predominant stages of change for HIV testing in both samples were precontemplation and contemplation. The stages of change correlated with two of the concurrent variables of self-efficacy and knowledge (p < ,01). The regression model was significant (F [3,296] = 53.68, p &...
18
artículo
Publicado 2017
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Tomopeas ravus, known as blunt - eared bat, is known only from thirteen confirmed localities in Peru and is currently listed as Endangered (B2 ab (iii)) by the IUCN. The distribution, occurrence extension and home range of this species is not have been completely clarified. We presents the first predictive model based on the known records and the first geographic approach to this species. On the basis of thirteen confirmed records we built a habitat model of maximum entropy determining previously the most important environmental variables for the model. An acceptable predictive index (0.970) was obtained for the final model. We determined the areas of major probability of occurrence for this species and felt the geographic distribution through the method of the polygon mínimum convex (PMC). The priority area identified for the conservation of this species is located in the northern of P...
19
artículo
Publicado 2020
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The aim of this study was to estimate genetic parameters and predict genetic merit for milk production adjusted to 305 days (PL) in crossbred cattle as selection criteria. Records of productive data was used from 289 purebred and crossbred animals with 349 lactations between 2000 and 2019. To obtain the PL, the incomplete gamma equation proposed by Woods was applied. The statistical and animal models included the random effects: additive genetic, permanent and temporary environments, while the fixed effects were breed composition, lactation and year of initiation of lactation. To analyze the variance components for the calculation of heritability (h2) and repeatability (r) for PL, the VCE v. 6.0 program was used and the breeding values through the animal model using the MTDFRELM software. Eleven inbred animals were reported with a mean inbreeding coefficient of 0.107 ± 0.115. The mean P...
20
artículo
Publicado 2020
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The aim of this study was to estimate genetic parameters and predict genetic merit for milk production adjusted to 305 days (PL) in crossbred cattle as selection criteria. Records of productive data was used from 289 purebred and crossbred animals with 349 lactations between 2000 and 2019. To obtain the PL, the incomplete gamma equation proposed by Woods was applied. The statistical and animal models included the random effects: additive genetic, permanent and temporary environments, while the fixed effects were breed composition, lactation and year of initiation of lactation. To analyze the variance components for the calculation of heritability (h2) and repeatability (r) for PL, the VCE v. 6.0 program was used and the breeding values through the animal model using the MTDFRELM software. Eleven inbred animals were reported with a mean inbreeding coefficient of 0.107 ± 0.115. The mean P...
