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Description:

Equação que identifica o ponto de inflexão de uma regressão e fragmenta os dados em dois conjuntos. Gerando assim gráficos e coeficientes de inclinação para os diferentes conjuntos de dados. Além de identificar se há diferença entre as inclinações das regressões.

Usage:

  compara_coefs (data, plota=F)

Arguments:

data: um data frame contendo as variáveis que se deseja analisar.

plota: identificador de qual gráfico se deseja como resultado (FALSE, RTS ou PSI).

Details:

Equação utilizada para segmentar uma regressão com possível variação entre os dados, como uma regressão exponencial.

Tem como resultado o ponto de inflexão que se divide a reta, além de informar os coeficientes de inclinação de cada uma das retas resultantes, e a diferença entre as inclinações.

Quando utilizado RTS dois gráficos das regressões são gerados para os diferentes conjuntos de dados separados pelo ponto de inflexão. Serão plotados também suas respectivas linhas de tendência. Exemplo:

Quando utilizado PSI, um gráfico é gerado com o conjunto de dados total, e uma linha de tendência fragmentada considerando o ponto de inflexão. Exemplo:

Author:

Iara Martins Ottoni

References:

Sokal, R.R., & Rohlf, F.J. Multiple and curvilinear regression. Pp. 609-684. In: Sokal, R.R., & Rohlf, F.J. (Eds.). Biometry. 1995. New York, NY. 850 p.

Paternoster, R., Brame, R., Mazerolle, P., & Piquero, A. R. 1998. Using the Correct Statistical Test for the Equality of Regression Coefficients. Criminology, 36(4), 859–866

Andrade JM, Estévez-Pérez MG. 2014. Statistical comparison of the slopes of two regression lines: a tutorial. Analytica Chimica Acta, 838:1–12.

Examples:

  x <- c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,1,2,2,1,2,1,2,2,2,2,2,1,2,2,1,3,1,3,1,2,1,2,2,3,3,2,3,3,3,2,3,3,2,1,5,5,1,4,3,4,3,3,5,7,2,4,6,4,4,3,6,5,5,3,4,3,4,7,5,7,11,3,6,6,6,9,1,1,3,9,3,4,6,6,12,6,2,12,8,2,4,12,6,8,9,6,5,4,4,11,4,18,8,10,8,17,5,16,16,6,5,18,3,1,10,2,11,21,8,11,15,9,13,14,3,11,17,18,9,16,17,12,18,2,9,17,14,14,5,21,21,13,17,15,9,1,18,17,7,2,17,23,22,27,10,10,17,25,12,28,12,13,14,5,20,13,3,17,16,21,11,27,19,19,19,22,19,6,30,16,13,10,30,18,17,30,4,23,20,18,5,22,10,37,38,19,36,36,34,37,36,25,30,26,22,32,30,30,45,18,25,42,44,24,38,34,14,16,6,36,26,29,28,44,20,31,45,39,43,46,47,34,46,47,40,48,43,49,46,48,49,49)
  y <-c(18.36734694,18.36734694,18.36734694,18.36734694,18.36734694,18.36734694,18.36734694,18.36734694,18.36734694,18.36734694,20.40816327,20.40816327,20.40816327,20.40816327,20.40816327,20.40816327,22.44897959,22.44897959,22.44897959,22.44897959,24.48979592,24.48979592,26.53061224,26.53061224,26.53061224,28.57142857,28.57142857,30.6122449,30.6122449,32.65306122,32.65306122,34.69387755,34.69387755,36.73469388,38.7755102,38.7755102,38.7755102,40.81632653,40.81632653,40.81632653,40.81632653,40.81632653,42.85714286,44.89795918,48.97959184,51.02040816,51.02040816,53.06122449,55.10204082,57.14285714,61.2244898,61.2244898,63.26530612,63.26530612,63.26530612,67.34693878,67.34693878,69.3877551,77.55102041,77.55102041,77.55102041,79.59183673,81.63265306,81.63265306,89.79591837,89.79591837,95.91836735,104.0816327,112.244898,124.4897959,130.6122449,134.6938776,138.7755102,146.9387755,146.9387755,151.0204082,161.2244898,163.2653061,165.3061224,167.3469388,169.3877551,169.3877551,169.3877551,171.4285714,181.6326531,185.7142857,208.1632653,220.4081633,224.4897959,230.6122449,240.8163265,240.8163265,246.9387755,267.3469388,269.3877551,271.4285714,304.0816327,306.122449,310.2040816,318.3673469,332.6530612,342.8571429,355.1020408,355.1020408,387.755102,395.9183673,395.9183673,397.9591837,404.0816327,430.6122449,448.9795918,451.0204082,455.1020408,465.3061224,465.3061224,467.3469388,469.3877551,518.3673469,522.4489796,528.5714286,532.6530612,534.6938776,534.6938776,553.0612245,563.2653061,569.3877551,577.5510204,583.6734694,583.6734694,600,612.244898,618.3673469,628.5714286,689.7959184,714.2857143,730.6122449,738.7755102,748.9795918,802.0408163,855.1020408,875.5102041,895.9183673,906.122449,924.4897959,934.6938776,948.9795918,955.1020408,977.5510204,989.7959184,997.9591837,1014.285714,1026.530612,1040.816327,1071.428571,1083.673469,1102.040816,1110.204082,1126.530612,1130.612245,1142.857143,1185.714286,1218.367347,1224.489796,1236.734694,1242.857143,1248.979592,1259.183673,1314.285714,1424.489796,1430.612245,1467.346939,1495.918367,1502.040816,1528.571429,1534.693878,1540.816327,1557.142857,1608.163265,1632.653061,1657.142857,1691.836735,1691.836735,1738.77551,1765.306122,1916.326531,1928.571429,2055.102041,2057.142857,2059.183673,2071.428571,2104.081633,2155.102041,2171.428571,2193.877551,2226.530612,2251.020408,2357.142857,2508.163265,2553.061224,2579.591837,2581.632653,2738.77551,2740.816327,2759.183673,2897.959184,2902.040816,2904.081633,2914.285714,3057.142857,3193.877551,3204.081633,3306.122449,3373.469388,3381.632653,3428.571429,3491.836735,3604.081633,3875.510204,4028.571429,4273.469388,4781.632653,5002.040816,5004.081633,5575.510204,5683.673469,6073.469388,6185.714286,6212.244898,6391.836735,6434.693878,6442.857143,6591.836735,6591.836735,6724.489796,6775.510204,8030.612245,8710.204082,9410.204082,9434.693878,9991.836735,10787.7551,11000,11048.97959,11524.4898,12085.71429,12881.63265,13620.40816,14087.7551,14089.79592,15636.73469,16361.22449,16440.81633,16759.18367,16846.93878,18267.34694,20240.81633,22004.08163,22816.32653,26493.87755,29981.63265,32777.55102,33724.4898,37240.81633,39116.32653,54540.81633,56977.55102,73912.2449)
  data <- data.frame(x,y)
  compara_coefs(data,plota = "RTS")
  compara_coefs(data,plota = "PSI")
  compara_coefs(data,plota = F)

Tabela de conteúdos