Search results for "mallit"
showing 10 items of 395 documents
Analyzing environmental‐trait interactions in ecological communities with fourth‐corner latent variable models
2021
In ecological community studies it is often of interest to study the effect of species related trait variables on abundances or presence-absences. Specifically, the interest may lay in the interactions between environmental and trait variables. An increasingly popular approach for studying such interactions is to use the so-called fourth-corner model, which explicitly posits a regression model where the mean response of each species is a function of interactions between covariate and trait predictors (among other terms). On the other hand, many of the fourth-corner models currently applied in the literature are too simplistic to properly account for variation in environmental and trait resp…
Blind source separation for non-stationary random fields
2022
Regional data analysis is concerned with the analysis and modeling of measurements that are spatially separated by specifically accounting for typical features of such data. Namely, measurements in close proximity tend to be more similar than the ones further separated. This might hold also true for cross-dependencies when multivariate spatial data is considered. Often, scientists are interested in linear transformations of such data which are easy to interpret and might be used as dimension reduction. Recently, for that purpose spatial blind source separation (SBSS) was introduced which assumes that the observed data are formed by a linear mixture of uncorrelated, weakly stationary random …
Estimating the causal effect of timing on the reach of social media posts
2022
AbstractModern companies regularly use social media to communicate with their customers. In addition to the content, the reach of a social media post may depend on the season, the day of the week, and the time of the day. We consider optimizing the timing of Facebook posts by a large Finnish consumers’ cooperative using historical data on previous posts and their reach. The content and the timing of the posts reflect the marketing strategy of the cooperative. These choices affect the reach of a post via a dynamic process where the reactions of users make the post more visible to others. We describe the causal relations of the social media publishing in the form of a directed acyclic graph, …
Premature conclusions about the signal‐to‐noise ratio in structural equation modeling research : A commentary on Yuan and Fang (2023)
2023
In a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller stan…
Estimating Mean Lifetime from Partially Observed Events in Nuclear Physics
2022
Abstract The mean lifetime is an important characteristic of particles to be identified in nuclear physics. State-of-the-art particle detectors can identify the arrivals of single radioactive nuclei as well as their subsequent radioactive decays (departures). Challenges arise when the arrivals and departures are unmatched and the departures are only partially observed. An inefficient solution is to run experiments where the arrival rate is set very low to allow for the matching of arrivals and departures. We propose an estimation method that works for a wide range of arrival rates. The method combines an initial estimator and a numerical bias correction technique. Simulations and examples b…
Bayesian Modeling of Sequential Discoveries
2022
We aim at modelling the appearance of distinct tags in a sequence of labelled objects. Common examples of this type of data include words in a corpus or distinct species in a sample. These sequential discoveries are often summarised via accumulation curves, which count the number of distinct entities observed in an increasingly large set of objects. We propose a novel Bayesian method for species sampling modelling by directly specifying the probability of a new discovery, therefore allowing for flexible specifications. The asymptotic behavior and finite sample properties of such an approach are extensively studied. Interestingly, our enlarged class of sequential processes includes highly tr…
bssm: Bayesian Inference of Non-linear and Non-Gaussian State Space Models in R
2021
We present an R package bssm for Bayesian non-linear/non-Gaussian state space modelling. Unlike the existing packages, bssm allows for easy-to-use approximate inference based on Gaussian approximations such as the Laplace approximation and the extended Kalman filter. The package accommodates also discretely observed latent diffusion processes. The inference is based on fully automatic, adaptive Markov chain Monte Carlo (MCMC) on the hyperparameters, with optional importance sampling post-correction to eliminate any approximation bias. The package implements also a direct pseudo-marginal MCMC and a delayed acceptance pseudo-marginal MCMC using intermediate approximations. The package offers …
Backcasting for desirable futures in Finnish forest-based firms
2020
Purpose In Finland, new forest-based sector (FBS) businesses are seen as important for the transition to the circular bioeconomy. The purpose of this study is to explore the transition of Finnish FBS companies to new business models. The aim is to understand how FBS companies define their ideal future states and related business models for the year 2030. Design/methodology/approach This study uses thematic interviews with managers from various FBS firms and companies from interfacing sectors. In the interviews, the key idea of backcasting was pursued when respondents discussed the desirable future states of their business. Findings The effort to achieve growth of the business and the appea…
Service platform implementation for simulation systems
2016
Nykyään olemassa olevia simulaatiojärjestelmiä hyödynnetään koneiden itseoppimisen ja tietojärjestelmäpohjaisten (KDD) alustojen kehityksessä. Tämän takia simulaatioiden merkitys ja vaikutus tulee kasvamaan suuressa määrin jokapäiväisessä elinympäristössämme. Yritykset kuten Ahphabet (Google), Facebook ja SpaceX edustavat yrityksinä kehitystä mallintamiseen ja simulointiin siirtyvästä tavasta kehittää MDA pohjaisia tuotteita itsenäisesti toimivista autoista avaruustutkimukseen. Ihmisen näkökulmasta nykyinen kehitys tulee muuttamaan ympäristöä tavalla, jossa kanssakäyminen koneiden kanssa muuttuu luonnolliseksi osaksi arkea. Tutkielman Tarkoituksena oli suunnitella ja toteuttaa palvelualusta…
The demand for IPR services - to use or not to use a professional representative
2021
We analysed the use of professional representative services and related outcomes in patent, utility model, design right and trademark filings. We found that: 1) there is a positive association between the use of a professional representative and the likelihood of grant or registration; 2) the demand for professional intellectual property rights (IPR) services is heterogeneous between IPR types: applicants are most likely to hire professional representatives (IPR agents and attorneys) for patents, followed by utility models, design rights and trademarks; 3) individual applicants are less likely to use professional representatives compared to firm applicants. peerReviewed