Linear Functional Form Research Articles

A Machine Learning Web Application to Estimate Listing Prices of South African Homes

Due to the heterogeneous nature of residential properties, determining selling prices which will reconcile supply and demand is difficult. Establishing realistic listing prices is vitally important for sellers to prevent prolonged time on market. Sellers have several resources available to assist in this endeavour, all of which involve understanding current market dynamics through analysing recent sales and listing data. Property portals which aggregate real estate agencies’ data, hosting it on online platforms, are one such resource, along with individual real estate agencies. Leveraging this data to develop solutions that could aid sellers in listing price decision making is a potential business objective that could not only add value to sellers but create a competitive advantage by increasing traffic to an online real estate platform. Using data provided by a South African online property portal, this paper creates a web application using machine learning to estimate listing prices for different types of homes throughout South Africa. This study compared log linear and gradient boosted models, estimating residential listing prices over a four-year period. The results indicate that although log linear models are suitable to account for spatial dependency in the data through the inclusion of a fixed location effect, the assumption of linear functional form was not satisfied. The gradient boosted models do not impose explicit functional form requirements, making them flexible candidates. Similarly, these models were able to handle the spatial dependency adequately. The gradient boosted models also achieved a lower out of sample error compared to the log linear models. The findings show that over observation periodperiod, larger properties consistently experience a diminishing return at some point over the marginal distribution of physical characteristics. The web application details how sellers are easily able to obtain mean listing price estimates and gauge the growth thereof, by simply inputting their property interest criteria.

On stability correction functions over the Indian region under stable conditions

AbstractTurbulence observations over an Indian region are used to examine the observational behaviour of stability‐correction functions for momentum ( φ m) and heat ( φ h) under stable conditions within the framework of Monin–Obukhov similarity theory. The φ m is observed to follow the linear functional form in the case of near‐neutral to moderately stable conditions. However, φ m is found to increase with a relatively slower rate as compared with the linear form in strongly stable conditions. A large scatter in φ h is observed with the near‐neutral condition, and they tend to level off in very stable conditions. The optimized co‐efficients appearing in the functional form of φ m suggested by Grachev et al. in 2007 are derived using turbulence observations. The present study recommends the use of these optimized functional forms of φ m and φ h for the estimation of surface fluxes over an Indian region in atmospheric models.

Comparative analysis of time-based and quadrat sampling in seasonal population dynamics of intermediate hosts of human schistosomes.

BackgroundDespite their importance for designing and evaluating schistosomiasis control trials, little attention in the literature has been dedicated to sampling protocols for the parasite’s snail intermediate hosts since their first development. We propose a comparative analysis of time-based and quadrat sampling protocols to quantify the seasonal variations in the abundance of these aquatic snail species of medical importance.Methodology/Principal findingsSnail populations were monitored during 42 consecutive months in three types of habitats (ephemeral pond, ephemeral river and permanent stream) in two sites covering different climatic zones in Burkina Faso. We employed both a widely used time-based protocol of 30min of systematic collection at a weekly interval, and a quadrat protocol of 8 replicates per sample at a monthly interval. The correspondence between the two protocols was evaluated using an ensemble of statistical models including linear and saturating-type functional forms as well as allowing for count zero-inflation. The quadrat protocol yielded on average a relative standard error of 40%, for a mean snail density of 16.7 snails/m2 and index of dispersion of 1.51. Both protocols yielded similar seasonal patterns in snail abundance, confirming the asynchrony between permanent and ephemeral habitats with respect to the country’s seasonal rainfall patterns. Formal model comparison of the link between time vs. quadrat counts showed strong support of saturation for the latter and measurement zero-inflation, providing important evidence for the presence of density feedbacks in the snail’s population dynamics, as well as for spatial clustering.Conclusions/SignificanceIn addition to the agreement with the time-based method, quadrat sampling provided insight into snail population dynamics and comparable density estimates across sites. The re-evaluation of these “traditional” sampling protocols, as well as the correspondence between their outputs, is of practical importance for the design and evaluation of schistosomiasis control trials.

Automatic Verification of GCD Constraint for Construction of Girth-Eight QC-LDPC Codes

As a general method to yield constructions for quasi-cyclic (QC) low-density parity-check (LDPC) codes with girth eight, the greatest-common-divisor (GCD) framework heavily relies on verifying a type of inequalities, referred to as GCD constraints. An algorithm is developed in this letter to automatically verify GCD constraints without conducting any manual analysis, by bounding from above the GCD of a fixed integer and an integer in the form of linear function. As an application of the algorithm, a set of novel constructions based on GCD framework is proposed. From these new constructions, four novel bounds on the size of circulant permutation matrices (CPMs) are formulated, such that girth-eight QC-LDPC codes always exist for any CPM size greater than or equal to the bounds. The new bound for column weight of 6 slightly improves the existing best one, and those for column weights from 7 to 9 significantly strengthen the state-of-the-art ones by decreasing from essentially a cubic or biquadratic power of row weight to a quadratic power of row weight.

Cost approach methodology in assessing economic stability of enterprise of hotel and restaurant sector

The article is devoted to improving the employment of cost approach methodology in assessing economic stability of enterprise of hotel and restaurant sector. The essence and the procedure of cost approach which allows calculating qualitative and quantitative value of every cost element and define its relative share in the total resource intensity have been investigated in the paper. It is determined that the most efficient strategic instrument for solving the issues of ensuring economic stability of the enterprise in hotel and restaurant sector is the vector-valued objective function. Its primary goal is to determine the object optimal for each specific criterion. Proceeding from the objective of ensuring sustainable economic growth, vector-valued objective function will include the assessment criteria – performance indicators and resource intensity indicators of operational activity of enterprise that maximize or minimize. The identified criteria assess various states of the analyzed object, with regard to which the decisions are approved. It has been substantiated that the use of economic stability assessment in the taxonomy on the basis of cost approach allows aggregating diversified indicators of the enterprise into a single indicator and identify the impact of various factors upon efficiency and, consequently, stability of the enterprise activity. It is determined that within the scope of the method of calculation by unit costs indicators between resultrelated and factor-related parameters the connection is employed in the form of proportional linear function. Such approximation cab be maintained only within narrow range of variation of resource intensity indicator. Therefore, for each range it is expedient to allocate its specific ‘per unit’ indicator. Assessment of dynamic economic sustainability of the enterprise is forecasted within a particular time period by means of determining residual variance or root-mean-square deviation indicator (sample variance). An algorithm is established with regard to the agenda for action that encompasses analysis, assessment, forecasting, optimization and serves as an instrument of managing the stability of the enterprise based upon cost monitoring and objective function. Realization of the object function with set restrictions contributes to forming the mechanism of sustainable development of the enterprise in the conditions of uncertainty and dynamic nature of external environment.

Wheat yield response to input and socioeconomic factors under changing climate: Evidence from rainfed environments of Pakistan

More than three-quarters of the world's total cultivated land is under rainfed farming, producing almost 70% of total food. Most food production comes from developing and least favored nations. Pakistan, a developing country with an agro-based economy, is facing severe threats from climate change. Rainfed agriculture, especially wheat farming, is highly susceptible due to its heavy dependency on precipitation, one of the most important climatic parameters. Wheat is the main food crop, as well as a major source of calorific intake, for millions of people in Pakistan. This study aims to quantify the impacts of climate variability on mean yield levels and yield variability of wheat crop in the rainfed zone of Pakistan. Multistage random sampling technique is used for primary data collection from 400 rainfed wheat farmers during the 2016–17 crop season. The study uses primary data on crop input-output, management, socioeconomic, institutional, and historical climatic data (1980–2017). The data are analyzed employing the Just and Pope (J-P) stochastic production function approach with linear and non-linear functional forms. The results reveal that temperature rise negatively affects observed wheat mean yields, while cumulative precipitation positively affected it. Further, input market access, seed rate, and cumulative precipitation also cause variability in yield levels, leading to yield instability. Further, farm elevation influences wheat mean yield positively while input market access influences it negatively. The findings of the study have important implications for climate resilient wheat farming. Timely and tailor-made adaptations need to be undertaken in the rainfed wheat farming systems of Pakistan. Creating awareness among farmers about the optimal use of agronomic inputs under changing climatic conditions could be an effective adaptation strategy that improves yields and copes with yield instability.

Additive generators of fuzzy operations in the form of linear fractional functions

This paper is devoted to the analysis of additive generators in the form of linear fractional functions. The limitations on the coefficients of increasing and decreasing generators are defined. It is shown that the compositions of increasing and/or decreasing generators are also generators. For each case, the corresponding triangular norms or conorms are found. It is established that the triangular norms and conorms obtained on the basis of linear fractional functions, and which are also dual to them, have the same structure. In fact, a new family of dual triangular norms and conorms is proposed.

Religiosity and Premarital Sexual Behaviors among Adolescents: An Analysis of Functional Form.

While numerous studies show a persistent inverse association between religion variables and adolescents' sexual behaviors, the nature of this relationship is not well understood. Specifically, many previous studies presuppose that the associations between adolescent religiosity and sexual behaviors are linear. However, a number of studies have also identified important nonlinearities of religious influence during adolescence, with highly religious individuals being distinct from their peers. Incorporating this knowledge into a theoretically-motivated modeling approach, this article provides a comparative analysis of functional forms describing the relationships between religiosity and adolescent sexual behaviors. Using data from two waves of the National Study of Youth and Religion, a linear functional form is compared with nonlinear alternatives that link multiple religion measures to outcomes of sexual activity. Results show that the majority of these relationships are best defined by nonlinear functional forms, suggesting that the influence of religiosity increases as individuals become more religious.

Correlates of Field Extension Workers’ Job Performance and SocioEconomic Variables in Akwaibom State, Nigeria

This study ascertained the correlates of extension workers job performance and socio-economic variables in Akwa Ibom State, Nigeria. The study utilized both primary and secondary data collected using a structured questionnaire. The sample size comprised 86 respondents, which included 56 extension agents, 14 Block Extension Agents, 14 Block Extension Supervisors and 2 Zonal Extension Officers. Data analyses involved descriptive statistics such as frequency counts, percentages, means and inferential statistics such as multiple regression analysis. A null hypothesis was tested at 5% level of significance. The result of the socio-economic characteristics of the respondents show that majority 50%, 35.7% and 44.6% of BESs, BEAs and EAs fall within active economic and productive age bracket of 35-44 years; while the ZEOs were between 45-54 years. Most of the ZEOs (100%), BESs (85.7%) and EAs (48.2%) were males; except among BEAs where majority (80%) were females. Greater proportion of 78.57%, 54.29% and 53.6% of BESs, BEAs and EAs were polytechnics and university graduates; who had worked for between 5-9 years with percentage values of 57.14%, 64.3% and 83.93% respectively. But, ZEOs had higher years of working experience of 15-19 and 20-24 years respectively. From the criteria considered, linear functional form was chosen as the lead equation; from where a high coefficient of multiple determinations R2 of 88.8% which showed a variation in the job performance of the extension workers due to their socio-economic characteristics was obtained. All the independent variables regressed where positively signed; while education and working experience where statistically significant at 1% and 5% levels respectively. The null hypothesis tested was rejected; which shows that the socio-economic characteristics of the field extension workers greatly influenced their job performance in the study area. This study had shown that the socio-economic attributes of extension workers greatly influenced their job performance in the study area. Extension Agents in the study area should be encouraged to further education as education was positively related to their job performance. Regular in-service training and short courses should be arranged for extension workers to create better awareness and upgrade their skills and knowledge in extension services delivery. More female extension workers should be employed and trained to improve their job performance in women in Agricultural activities.

Data analysis and forecasting of tourism development in Ukraine

The article contains a thorough study of tourist flows in Ukraine during the last 18 years. The tendencies of the development of international tourism during the last 20 years and their influence on the development of tourism in Ukraine have been explored. Particular attention is paid to the analysis of inbound tourist flows. The negative dynamics of tourist arrivals in Ukraine led to the construction of a forecast model for the development of this component of tourism activity with the aim of an objective assessment of future tourist arrivals and the adoption of effective management decisions on improving the situation of tourism in Ukraine. Tourist destinations today are rigorously competing for consumer interest in tourism products. In view of this, tourist facilities operating in the tourist market place particular emphasis on the elements of tourism marketing (product, price, distribution, advertising, human capital, actual data, processes).Modern forecasting systems and methods have been used to build a forecast of tourism development in Ukraine and, in particular, arrivals of foreign tourists to Ukraine. An analytical forecasting model was built by the system of CurveExpert in the form of a polynomial function, analytical forecasting models were built by the system of computer algebra Maple in the form of piecewise linear and piecewise polynomial functions. Numerical prediction models in the MathCAD system using different types of spline-interpolation and predictive functions have been constructed. A comparative analysis of the results of forecasting in different systems was carried out. The results of the comparative analysis give confidence in the development of inbound tourism in Ukraine.

Price convergence in the UK supermarket chains: Evidence from nonlinear cointegration approach

Supermarket chain is an important sector of the UK grocery stores and the growing dominance of supermarket chains has brought public concern over exploitation of market power in the UK retail grocery industry. This paper therefore aims to examine the price convergence of the UK supermarket products. Since the cointegrating relationship between supermarket prices may not be exact or linear, we adopt the rank tests for analysis which do not require prior knowledge and specification of the linear or nonlinear functional form. Our results confirm the evidence of the price convergence of all grocery products and then validate the price competition between the UK supermarket chains. Furthermore, a subset of the cointegration relationships exhibits nonlinear long-run price co-movements.

Generalised clusterwise regression for simultaneous estimation of optimal pavement clusters and performance models

ABSTRACT This paper focuses on clusterwise regression (CR) approach for modelling of pavement performance. CR simultaneously clusters the data and estimates the associated models. Previous studies using CR approach have a few limitations: (1) the explanatory power of variables used in the analyses was not tested; (2) the approach could not find the optimal number of clusters; (3) the objective function was to minimise the sum of squared errors, which is not the best to seek for the optimal number of clusters; (4) the model functional form was restricted to be either linear or nonlinear. To address these limitations, this paper proposes a generalised mathematical programme and solution algorithm within the CR framework. Bayesian Information Criteria was used as the objective function. The proposed approach explored all possible combinations of potential significant explanatory variables to select the best model specification. The potential multicollinearity issues in the models were addressed if required. Both linear and nonlinear functional forms were estimated using a large dataset in Nevada. Predictive accuracy of the resultant models was evaluated using root-mean-square error (RMSE), normalised RMSE, and mean absolute errors. The results showed that the nonlinear models were more accurate than the linear models in estimating present serviceability index.

Seismic response prediction of reinforced concrete buildings through nonlinear combinations of intensity measures

A widespread approach for the prediction of the structural response as function of the ground motion intensity is based on the Cloud Analysis: once a set of points representing the engineering demand parameter (EDP) values is obtained as function of the selected seismic intensity measure (IM) for a collection of unscaled earthquake records, a regression analysis is performed by assuming a specific functional form to correlate these variables. Within this framework, many studies have been devoted so far to evaluate the effectiveness of several IMs in estimating the EDPs through intrinsically linear functional forms, but it is still unknown to what extent the use of the linear regression analysis affects the quality of the final results. This paper is intended to provide an answer to such question by means of the calibration of suitable nonlinear combinations of scalar IMs, whose statistical performances are compared with those obtained by using the functional form usually adopted for linear regression-based calibrations. Specifically, the Evolutionary Polynomial Regression technique is adopted to calibrate nonlinear regression models for the prediction of maximum inter-story drift ratio and maximum floor acceleration. The comparative analysis is performed for fixed-base and base-isolated reinforced concrete buildings subjected to ordinary or pulse-like ground motion taking into account accuracy, complexity, efficiency and sufficiency. Final results demonstrate that the linear regression analysis is suitable for fixed-base reinforced concrete buildings, but nonlinear regression models provide better estimates. On the other hand, the linear regression analysis can introduce a significant bias in the seismic response prediction of base-isolated buildings, and nonlinear regression models are deemed more appropriate.

Statistical power for the comparative regression discontinuity design with a nonequivalent comparison group.

In the "sharp" regression discontinuity design (RD), all units scoring on one side of a designated score on an assignment variable receive treatment, whereas those scoring on the other side become controls. Thus the continuous assignment variable and binary treatment indicator are measured on the same scale. Because each must be in the impact model, the resulting multi-collinearity reduces the efficiency of the RD design. However, untreated comparison data can be added along the assignment variable, and a comparative regression discontinuity design (CRD) is then created. When the untreated data come from a non-equivalent comparison group, we call this CRD-CG. Assuming linear functional forms, we show that power in CRD-CG is (a) greater than in basic RD; (b) less sensitive to the location of the cutoff and the distribution of the assignment variable; and that (c) fewer treated units are needed in the basic RD component within the CRD-CG so that savings can result from having fewer treated cases. The theory we develop is used to make numerical predictions about the efficiency of basic RD and CRD-CG relative to each other and to a randomized control trial. Data from the National Head Start Impact study are used to test these predictions. The obtained estimates are closer to the predicted parameters for CRD-CG than for basic RD and are generally quite close to the parameter predictions, supporting the emerging argument that CRD should be the design of choice in many applications for which basic RD is now used. (PsycINFO Database Record

TSFLC based DC link voltage regulation of grid connected DC micro grid

Integration of micro grid with utility power network has major concerns such as active power control and maintaining desired power quality (PQ) standards. Among several power quality issues, voltage dip and harmonics are critical concerns impacting the overall performance and stability of system. In this paper, a grid connected DC micro grid (DCMG) is designed and controlled to ensure requisite power allocation between the micro-grid and utility grid system vis-à-vis DC link voltage regulation, load balancing and harmonic elimination. The utility grid and DCMG system are interfaced via voltage source converter (VSC). The DC link voltage of VSC is regulated using Takagi-Sugeno fuzzy logic controller (TSFLC) based synchronous reference frame technique to compensate for the reactive power demanded by the load. In the proposed architecture, DCMG consists of 8 kW photovoltaic (PV) energy system with maximum power point tracking (MPPT), 6 kW wind energy generation system with MPPT, 3 kW fuel cell (FC) energy systems and a VSC interfaced to three phase utility grid. Further, the TSFLC is compared with conventional PI controller under different operating conditions. It has advantages over classical controller such as better performance under dynamics and can be expressed in the form of the exact linear function. The effectiveness of proposed control method is validated under MALAB/SIMULINK software under different loading conditions.

TSFLC based DC link voltage regulation of grid connected DC micro grid

Integration of micro grid with utility power network has major concerns such as active power control and maintaining desired power quality (PQ) standards. Among several power quality issues, voltage dip and harmonics are critical concerns impacting the overall performance and stability of system. In this paper, a grid connected DC micro grid (DCMG) is designed and controlled to ensure requisite power allocation between the micro-grid and utility grid system vis-a-vis DC link voltage regulation, load balancing and harmonic elimination. The utility grid and DCMG system are interfaced via voltage source converter (VSC). The DC link voltage of VSC is regulated using Takagi-Sugeno fuzzy logic controller (TSFLC) based synchronous reference frame technique to compensate for the reactive power demanded by the load. In the proposed architecture, DCMG consists of 8 kW photovoltaic (PV) energy system with maximum power point tracking (MPPT), 6 kW wind energy generation system with MPPT, 3 kW fuel cell (FC) energy systems and a VSC interfaced to three phase utility grid. Further, the TSFLC is compared with conventional PI controller under different operating conditions. It has advantages over classical controller such as better performance under dynamics and can be expressed in the form of the exact linear function. The effectiveness of proposed control method is validated under MALAB/SIMULINK software under different loading conditions.

Trends of area, production and productivity of turmeric in Assam

Turmeric is an important spice crop grown in Assam. The present study is an attempt to study the trends of turmeric in terms of area, production and productivity in the state of Assam. In order to study the trends of turmeric, the secondary data regarding area, production and productivity of turmeric for the period 1976–77 to 2014–15 were collected from various publications. To analyze the trend of area, production and productivity of turmeric, the linear, quadratic and exponential functional forms were selected. Finally quadratic function was used in the study to estimate the trend of turmeric based on highest R2 value. Besides, compound growth rate, coefficient of variation, instability index and interaction effect of area and productivity and their interaction effect on increasing production were also estimated in the present study. The results revealed that the ‘C’ value in the quadratic functional form for area, production and productivity, which were positive and significant for turmeric crop. This implies the acceleration of growth of area, production and productivity of the crop in the State.

Valoración económica de la demanda del servicio ambiental hídrico del bosque de la micro cuenca Madriguera, Siuna-Nicaragua

Este estudio estimó la disponibilidad a pagar (DAP) de las familias residentes en el área urbana del municipio de Siuna, que reciben agua para consumo diario de la microcuenca Madriguera, por la mejora en la oferta hídrica, mediante el método de valoración contingente y el uso de formato binario. Se estimaron medidas de cambio en el bienestar a través de estimaciones paramétricas en la forma funcional lineal. Asimismo, se calcularon los componentes del valor económico total que los beneficiarios asignan al recurso hídrico proveniente del bosque de la microcuenca. Los resultados de la disposición a pagar (DAP), han revelado que las viviendas que tienen fuente hídrica alterna, tienen una menor disposición a pagar y viceversa. Una alta proporción de la población está dispuesta a pagar y lo hacen de acuerdo a los tipos de valor económico de uso directo y herencia. Quienes no están dispuestos a pagar es porque no tienen recursos económicos. El valor mínimo como medida de cambio de bienestar es de C$116.29 (Ciento dieciséis con 29córdobas). Ello implica la cantidad de C$ 74, 890.76 mensuales para un total de C$ 898, 689.12 anualmente. Los beneficiarios reconocen la importancia del bien y se justifica su valoración en cuanto a que el servicio ambiental de la microcuenca les genera bienestar y favorecen la idea de implementar proyectos de protección y conservación para evitar un cambio desfavorable.

Modeling the effects of standardized ileal digestible isoleucine to lysine ratio on growth performance of nursery pigs1,2

Two experiments evaluated the effects of increasing standardized ileal digestible (SID) Ile:Lys ratio on growth performance of nursery pigs. In both experiments, dietary treatments consisted of 40, 44, 48, 52, 54, 58, or 63% SID Ile:Lys ratio. Diets were formulated using analyzed ingredient AA values and NRC (2012) SID coefficients. A combination of field peas and spray dried blood cells were used to ensure a low enough Ile diet concentration while minimizing the excess of Leu. The experiments consisted of 8 pens per dietary treatment with 5 pigs per pen for a total of 280 nursery pigs per experiment (Exp. 1: PIC 327 × 1,050, initially 6.7 ± 1.0 kg BW; Exp. 2: DNA 600 × 241, initially 6.0 ± 0.97 kg BW). Data were analyzed using mixed models with heterogeneous variance, where appropriate. The dose response was further characterized using quadratic polynomial (QP), broken-line linear (BLL), or broken-line quadratic (BLQ) functional forms. For Exp. 1, diets were initiated 6-d post-weaning and fed for 12-d followed by a common diet from d 12 to 28. From d 0 to 12, increasing dietary SID Ile:Lys ratio increased ADG (linear, P < 0.005) and ADFI (quadratic, P < 0.017) but G:F decreased (quadratic, P < 0.043). For ADG, the QP, BLL, and BLQ models resulted in maximum ADG at 64.7, 52.0, and 52.0 SID Ile:Lys ratios, respectively. For ADFI, the BLL breakpoint occurred at 50.6 and the QP predicted maximum ADFI at 56.2 SID Ile:Lys ratio. In Exp. 2, diets were initiated 6-d post-weaning for 7 pens and 3-d post-weaning for one heavier block and fed for 18-d followed by a common diet from d 18 to 32. From d 0 to 18, ADG and ADFI increased (quadratic, P < 0.016) with no evidence for difference in G:F as SID Ile:Lys ratio increased. For ADG, the QP and BLL had similar fit with breakpoints or maximums occurring at 58.3 and 51.8% SID Ile:Lys ratio, respectively. For ADFI, the BLQ breakpoint occurred at 52.0 SID Ile:Lys and the QP maximum ADFI at 57.2% SID Ile:Lys ratio. In conclusion, broken-line models reported maxima of 52.0% Ile:Lys ratio while quadratic models were as high as 64% of Lys to maximize ADG and ADFI of 6- to 11-kg nursery pigs. However, for the QP models 99% of the maximum response was achieved with a dose comparable to that from the broken line models. Therefore, these results are similar to the NRC (2012) requirement estimate of 51.1 Ile:Lys ratio.

Seventy years of stream‐fish collections reveal invasions and native range contractions in an Appalachian (USA) watershed

AbstractAimKnowledge of expanding and contracting ranges is critical for monitoring invasions and assessing conservation status, yet reliable data on distributional trends are lacking for most freshwater species. We developed a quantitative technique to detect the sign (expansion or contraction) and functional form of range‐size changes for freshwater species based on collections data, while accounting for possible biases due to variable collection effort. We applied this technique to quantify stream‐fish range expansions and contractions in a highly invaded river system.LocationUpper and middle New River (UMNR) basin, Appalachian Mountains, USA.MethodsWe compiled a 77‐year stream‐fish collections dataset partitioned into ten time periods. To account for variable collection effort among time periods, we aggregated the collections into 100 watersheds and expressed a species’ range size as detections per watershed (HUC) sampled (DPHS). We regressed DPHS against time by species and used an information‐theoretic approach to compare linear and nonlinear functional forms fitted to the data points and to classify each species as spreader, stable or decliner.ResultsWe analysed changes in range size for 74 UMNR fishes, including 35 native and 39 established introduced species. We classified the majority (51%) of introduced species as spreaders, compared to 31% of natives. An exponential functional form fits best for 84% of spreaders. Three natives were among the most rapid spreaders. All four decliners were New River natives.Main conclusionsOur DPHS‐based approach facilitated quantitative analyses of distributional trends for stream fishes based on collections data. Partitioning the dataset into multiple time periods allowed us to distinguish long‐term trends from population fluctuations and to examine nonlinear forms of spread. Our framework sets the stage for further study of drivers of stream‐fish invasions and declines in the UMNR and is widely transferable to other freshwater taxa and geographic regions.